Дисертації з теми "Layout problem"

Thesis (Ph. D.)--West Virginia University, 2007.
Title from document title page. Document formatted into pages; contains xi, 86 p. : ill. Includes abstract. Includes bibliographical references (p. 82-86).

Thesis (Ph. D.)--University of Oregon, 1999.
Typescript. Includes vita and abstract. Includes bibliographical references (leaves 168-173). Also available for download via the World Wide Web; free to University of Oregon users. Address: http://wwwlib.umi.com/cr/uoregon/fullcit?p9948030.

The facilities layout problem, which is an integral part of facilities design, aims to spatially locate the production units within a facility subject to some design criteria and area limitations, with one or multiple objectives. In this study, the layout problem is reviewed in detail, with an emphasis on the dynamic environment it operates in. Despite the fact that layouts within the context of changing manufacturing requirements represent the problem better, the single period block layout problem is observed to have remained worth analyzing. In this thesis, a hybrid model that combines the strong aspects of the available models in the literature is constructed for the single period block layout problem. The LP relaxation of this model and the effect of adding valid inequalities to the model are studied. A rounding heuristic based on the LP relaxation of the problem is proposed and computational experimentation is made. Also, an evolutionary algorithm scheme that uses the sequence pair representation is proposed. Three mutation operators are developed to be used in this scheme. Preliminary test are made for implementations of these operators and results are given.

Thesis (M.S.)--West Virginia University, 2005.
Title from document title page. Document formatted into pages; contains vii, 88 p. : ill. Includes abstract. Includes bibliographical references (p. 83-88).

In today’s dynamic environment, where product demands are highly volatile and unstable, the ability to design and operate manufacturing facilities that are robust with respect to uncertainty and variability is becoming increasingly important to the success of any manufacturing firm in order to operate effectively in such an environment. Hence manufacturing facilities must be able to exhibit high levels of robustness and stability in order to deal with changing market demands. In general, Facility Layout Problem (FLP) is concerned with the allocation of the departments or machines in a facility with an objective to minimize the total material handling cost (MHC) of moving the required materials between pairs of departments. Most FLP approaches assume the flow between departments is deterministic, certain and constant over the entire time planning horizon. Changes in product demand and product mix in a dynamic environment invalidate these assumptions. Therefore there is a need for stochastic FLP approaches that aim to assess the impact of uncertainty and accommodate any possible changes in future product demands.This research focuses on stochastic FLP with an objective to present a methodology in the form of a framework that allows the layout designer to incorporate uncertainty in product demands into the design of a facility. In order to accomplish this objective, a measure of impact of this uncertainty is required. Two solution methods for single and multi period stochastic FLPs are presented to quantify the impact of product demand uncertainty to facility layout designs in terms of robustness (MHC) and variability (standard deviation). In the first method, a hybrid (simulation) approach which considers the development of a simulation model and integration of this model with the VIPPLANOPT 2006 algorithm is presented. In the second method, mathematical formulations of analytic robust and stable indices are developed along with the use of VIPPLANOPT for solution procedure. Several case studies are developed along with numerical examples and case studies from the literature are used to demonstrate the proposed methodology and the application of the two methods to address different aspects of stochastic FLP both analytically and via the simulation method. Through experimentation, the proposed framework with solution approaches has proven to be effective in evaluating the robustness and stability of facility layout designs with practical assumptions such as deletion and expansion of departments in a stochastic environment and in applying the analysis results of the analytic and simulation indices to reduce the impact of errors and make better decisions

Thesis (M.S.)--West Virginia University, 2001.
Title from document title page. Document formatted into pages; contains x, 133 p. : ill. Includes abstract. Includes bibliographical references (p. 88-94).

Thesis (M.S.)--West Virginia University, 2002.
Title from document title page. Document formatted into pages; contains vii, 76 p. : ill. Includes abstract. Includes bibliographical references (p. 72-76).

The facility layout design problem is concerned with determining the arrangement and configuration of facilities, which optimizes a prescribed objective such as profit, cost, or distance, and which satisfies various prescribed constraints pertaining to available resources. In industry, facility layout design problems arise in manufacturing, in warehousing, and in various assignment type situations. The solution of these problems impacts on the viability of the industry. For example, material-handling costs which can comprise between 30 and 75% of the total manufacturing costs, can be reduced by using the optimization methods associated with the facility layout design. In the service industries, facility layout design problems arise in the location of emergency facilities (such as ambulance, fire stations) and in the allocation of space. The solution of these location problems impacts on the well being of the community. Mathematically, the facility layout problem has been modelled as: a quadratic assignment problem, a quadratic set covering problem, a linear integer programming problem, a mixed integer programming problem, and a graph theoretic problem. The problem has been shown to be NP-complete. This computational difficulty has led researchers to consider suboptimal solutions generated by heuristic approaches. There are a number of heuristic procedures that have been proposed for solving the facility layout design problem, including Simulated Annealing, Tabu Search, Expert Systems, and Graph Theoretic Algorithms. The most successful heuristic approaches are based on graph theoretic concepts. In this thesis we focus our study on constructive graph theoretic based heuristics for determining an optimal arrangement and configuration of facilities with the objective of maximizing the total benefit.We are particularly interested in constructive heuristics, which can produce a maximum-weighted planar graph as a final solution. Our contribution is the development, implementation, and testing of three new algorithms. Computational results, based on 4200 randomly (uniform and normal distribution) generated problems, demonstrate the value of our methods. We also present the performance of each algorithm when various initial solutions are applied. Chapter 1 provides the background of the facility layout design, including the notation, terminology and general concepts as well as a summary of the thesis. Chapter 2 provides a comprehensive survey of the facility layout design problem. This includes models and methods of solution based on exact algorithms (including the branch and bound method and the cutting plane method), as well as heuristic algorithms. We detail the main constructive graph theoretic based heuristics in the literature: the Deltahedron Method, the Green-Al Hakim Algorithm, the Leung’s Constructive Heuristic, the Kim-Kim Algorithm, the Wheel Expansion Method, TESSA and the String Processing Algorithm. We also briefly discuss the non-graph theoretic heuristics including simulated annealing, tabu search, and expert systems. In Chapter 3 we present three new graph theoretic based heuristics. These heuristics are constructive and the solution is built up, starting with an initial layout of four facilities, by an insertion process. Our algorithms have two important features. Firstly, they allow for previously chosen edges to be removed at each insertion step. Secondly, they do not restrict the type of maximal planar graph produced. Computational results and a comparative analysis of the main graph theoretic based heuristics are provided. The analysis is based on 4200 randomly generated test problems (from uniform and normal distribution).The test problems consist of 30 data sets with the number of facilities ranging from 5 to 100 in increments of 5. Chapter 4 is devoted to the performance of graph theoretic based heuristics when different types of initial solutions are applied. Examples show that the final solution is sensitive to the initial solution. Computational results indicate that for most algorithms, the best type of initial solution is the selection of four facilities which yield the best objective function value contribution. However, this does not always coincide with that proposed in the original description of the algorithms. We conclude this thesis by discussing some future research that can be carried out on the facility layout design problem, particularly in graph theoretic based heuristics.

The facility layout design problem is concerned with determining the arrangement and configuration of facilities, which optimizes a prescribed objective such as profit, cost, or distance, and which satisfies various prescribed constraints pertaining to available resources. In industry, facility layout design problems arise in manufacturing, in warehousing, and in various assignment type situations. The solution of these problems impacts on the viability of the industry. For example, material-handling costs which can comprise between 30 and 75% of the total manufacturing costs, can be reduced by using the optimization methods associated with the facility layout design. In the service industries, facility layout design problems arise in the location of emergency facilities (such as ambulance, fire stations) and in the allocation of space. The solution of these location problems impacts on the well being of the community. Mathematically, the facility layout problem has been modelled as: a quadratic assignment problem, a quadratic set covering problem, a linear integer programming problem, a mixed integer programming problem, and a graph theoretic problem. The problem has been shown to be NP-complete. This computational difficulty has led researchers to consider suboptimal solutions generated by heuristic approaches. There are a number of heuristic procedures that have been proposed for solving the facility layout design problem, including Simulated Annealing, Tabu Search, Expert Systems, and Graph Theoretic Algorithms. The most successful heuristic approaches are based on graph theoretic concepts. In this thesis we focus our study on constructive graph theoretic based heuristics for determining an optimal arrangement and configuration of facilities with the objective of maximizing the total benefit.
We are particularly interested in constructive heuristics, which can produce a maximum-weighted planar graph as a final solution. Our contribution is the development, implementation, and testing of three new algorithms. Computational results, based on 4200 randomly (uniform and normal distribution) generated problems, demonstrate the value of our methods. We also present the performance of each algorithm when various initial solutions are applied. Chapter 1 provides the background of the facility layout design, including the notation, terminology and general concepts as well as a summary of the thesis. Chapter 2 provides a comprehensive survey of the facility layout design problem. This includes models and methods of solution based on exact algorithms (including the branch and bound method and the cutting plane method), as well as heuristic algorithms. We detail the main constructive graph theoretic based heuristics in the literature: the Deltahedron Method, the Green-Al Hakim Algorithm, the Leung’s Constructive Heuristic, the Kim-Kim Algorithm, the Wheel Expansion Method, TESSA and the String Processing Algorithm. We also briefly discuss the non-graph theoretic heuristics including simulated annealing, tabu search, and expert systems. In Chapter 3 we present three new graph theoretic based heuristics. These heuristics are constructive and the solution is built up, starting with an initial layout of four facilities, by an insertion process. Our algorithms have two important features. Firstly, they allow for previously chosen edges to be removed at each insertion step. Secondly, they do not restrict the type of maximal planar graph produced. Computational results and a comparative analysis of the main graph theoretic based heuristics are provided. The analysis is based on 4200 randomly generated test problems (from uniform and normal distribution).
The test problems consist of 30 data sets with the number of facilities ranging from 5 to 100 in increments of 5. Chapter 4 is devoted to the performance of graph theoretic based heuristics when different types of initial solutions are applied. Examples show that the final solution is sensitive to the initial solution. Computational results indicate that for most algorithms, the best type of initial solution is the selection of four facilities which yield the best objective function value contribution. However, this does not always coincide with that proposed in the original description of the algorithms. We conclude this thesis by discussing some future research that can be carried out on the facility layout design problem, particularly in graph theoretic based heuristics.

Thesis (Ph.D.) - University of Waterloo, 2001.
"A thesis presented to the University of Waterloo in fulfilment of the thesis requirement for the degree of Doctor of Philosophy in Combinatorics and Optimization". Includes bibliographical references. Also available in microfiche format.

Thesis (Ph. D.)--West Virginia University, 2008.
Title from document title page. Document formatted into pages; contains xiii, 109 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 97-103).

In this thesis, we study both dynamic and distributed facility layout problems, where the demand for product mix changes over time. We propose a new simulated annealing algorithm, SALAB, for the dynamic facility layout problem. Four variants of SALAB find the best known solution for 20 of the 48 benchmark problems from the literature, improving upon the best known solutions of 18 problems. We modify SALAB to obtain DSALAB, solving the dynamic distributed facility layout problem with the objective of minimizing relocation cost and total (full and empty) travel cost of the material handling system. We simulate DSALAB solutions of randomly generated problems to study the tradeoff between total cost and congestion in the system. Our experimental results indicate that distributing the department duplicates throughout the facility reduces the total cost with diminishing returns and causes increasing congestion. Therefore, distribution beyond a certain level is not justified.

L'agencement d'espace est un problème courant dans la plupart des secteurs industriels. Ce problème est de nature continue et discret et il est considéré comme un problème NP-difficile. Les méthodes d'optimisation traditionnelles, plus appropriées pour une recherche locale sont difficilement utilisables aux problèmes d'agencement. Afin de contourner ces limitations inhérentes aux méthodes classiques, nous proposons deux algorithmes adaptés aux problèmes d'agencement statique de composants de différentes tailles. Pour les problèmes d'agencement considérés, les fonctions objectives à minimiser sont non linéaires et représentent les coûts associés aux sommes pondérées des distances entre les composants. La première approche que nous considérons est une méthode hybride en deux étapes. La première étape consiste à construire un agencement en se basant sur la méthode dite "bas-gauche" comme une solution locale. Ensuite, la solution obtenue est améliorée en appliquant un algorithme génétique modifié. Les opérateurs de croisement et de mutation sont alors adaptés pour prendre en compte les spécificités du problème d'agencement. La deuxième approche est une combinaison entre une recherche locale et globale. Dans ce cas, l'algorithme génétique est également modifié par l'introduction d'un opérateur spécialisé pour le traitement des rotations des composants. Il permet notamment d'éviter le couplage entre les variables réelles et entières et permet également de réduire considérablement le nombre de variables du problème d'optimisation. Les performances des deux approches sont testées et comparées avec les exemples de référence extraits des publications traitant du problème d'optimisation d'agencement. Nous démontrons que les deux approches que nous proposons obtiennent de meilleures performances que les approches existantes
A facility layout design is one of the most commonly faced problems in the manufacturing sectors. The problem is mixed-integer in nature and usually an NP-hard problem, which makes it difficult to solve using classical optimization techniques, which are better for local search. To overcome these limitations, two algorithms have been proposed for solving static facility layout problems with the unequal size compartments. The objective function of the problems considered is nonlinear in which the sum of the material handling cost has been minimized. In the first approach, a hybrid constructive and improvement model has been proposed where an advanced bottom-left fill technique was used as constructive approach. The constructive model proposed also acts as a local search method based on greedy algorithm. For improvement approach a hybrid genetic algorithm has been proposed, where the crossover and mutation operator are specially designed to handle the solution representation which itself is used as constructive model. In the second approach, a combined local and global search model was proposed where a rotation operator was used to avoid mixed-integer formulation of the problem. Use of rotation operator has also reduced the number of variables significantly. Apart from the conventional evolutionary operators this model has also used exchange and rotation operators. The performances of both model are tested over a previously solved problem selected from the literature. The evaluation of the results shows that the performances of the proposed models are better than many existing algorithms and has the potential for field applications

The diploma thesis focuses on tracing in layout by handlers between assembly lines in new plant for corporation Continental Automotive Czech Republic ltd, where boosters are produced. The theoretical part involves definitions of logistics, supply chain, material flow and handling equipment. Furthermore, methods of mathematic programming and software equipment are described, such as quadratic assignment problem, knapsack problem, travelling salesman problem from graph theory. In the practical part the situation in corporation has been analyzed and the data prepared for further examination. Then layout of plant and internal processes are evaluated and an appropriate model or concept of solution is selected. Subsequently, application in MS Excel is created with support of VBA scripts (3 kinds of layouts). The user manipulates with application followed by Solver for implementation of a new solution into practice. Finally, the models are interpreted and verified by Lingo. The focus of the thesis is the design of a layout change of a new plant including the description of tracing.

Data in real-world graph drawing applications often change frequently but incrementally. Any drastic change in the graph layout could disrupt a user's "mental map." Furthermore, real-world applications like enterprise process or e-commerce graphing, where data change rapidly in both content and quantity, demand a comprehensive responsiveness when rendering the graph layout in a multi-user environment in real time. Most standard static graph drawing algorithms apply global changes and redraw the entire graph layout whenever the data change. The new layout may be very different from the previous layout and the time taken to redraw the entire graph degrades quickly as the amount of graph data grows. Dynamic behavior and the quantity of data generated by real-world applications pose challenges for existing graph drawing algorithms in terms of incremental stability and scalability. A constrained hierarchical graph drawing framework and modified Sugiyama heuristic were developed in this research. The goal of this research was to improve the scalability of the constrained graph drawing framework while preserving layout stability. The framework's use of the relational data model shifts the graph application from the traditional desktop to a collaborative and distributed environment by reusing vertex and edge information stored in a relational database. This research was based on the work of North and Woodhull (2001) and the constrained crossing reduction problem proposed by Forster (2004). The result of the constrained hierarchical graph drawing framework and the new Sugiyama heuristic, especially the modified barycenter algorithms, were tested and evaluated against the Graphviz framework and North and Woodhull's (2001) online graph drawing framework. The performance test results showed that the constrained graph drawing framework run time is comparable with the performance of the Graphviz framework in terms of generating static graph layouts, which is independent of database accesses. Decoupling graph visualization from the graph editing modules improved scalability, enabling the rendering of large graphs in real time. The visualization test also showed that the constrained framework satisfied the aesthetic criteria for constrained graph layouts. Future enhancements for this proposed framework include implementation of (1) the horizontal coordinate assignment algorithm, (2) drawing polylines for multilayer edges in the rendering module, and (3) displaying subgraphs for very large graph layouts.

Thesis (M.S.)--West Virginia University, 2002.
Title from document title page. Document formatted into pages; contains xi, 87 p. : ill. Includes abstract. Includes bibliographical references (p. 84-87).

Nowadays, assembly robots are increasingly used in the manufacturing industry to replace or collaborate with human labors. This is the goal of the dual arm assembly robot developed by ABB. With the rapid upgrading in consumer electronics products, the lifetime of an assembly line could be only a few months. However, even for experienced programmers, to manually construct a good enough assembly sequence is time consuming, and the quality of the generated assembly sequence is not guaranteed. Moreover, a good robot assembly sequence is important to the throughput of an assembly line. For dual arm robots, it is also important to obtain a balance between the two arms, as well as handling scheduling conflicts and avoiding collisions in a crowded environment. In this master thesis, a program is produced to automatically generate the optimal assembly sequence for a class of real-world assembly cases. The solution also takes the layout of the assembly cell into account, thus constructing the best combination of cell layout, workload balancing, task sequence and task scheduling. The program is implemented using Google OR-Tools – an open-source support library for combinatorial optimization. A customized search strategy is proposed and a comparison between this strategy and the built-in search strategy of Google OR-Tools is done. The result shows that the used approach is effective for the problem study case. It takes about 4 minutes to find the optimal solution and 32 minutes to prove its optimality. In addition, the result also shows that the customized search strategy works consistently with good performance for different problem cases. Moreover, the customized strategy is more efficient than built-in search strategy in many cases.
Numera används monteringsrobotar alltmer inom tillverkningsindustrin för att ersätta eller samarbeta med människor. Detta är måluppgiften för den tvåarmiga monteringsroboten, YuMi, som utvecklats av ABB. Med den korta produktlivslängden för hemelektronikprodukter kan livslängden för en monteringslinje vara ett fåtal månader. Även för erfarna robotprogrammerare är det svårt och tidsödande att manuellt konstruera en tillräckligt bra monteringsordning, och dessutom kan resultatets kvalitet inte garanteras. En bra monteringsordning är nödvändig för genomströmningen i en monteringslinje. För tvåarmiga robotar, är det också viktigt att få en balans mellan de två armarna, samt hantering av schemakrockar och undvika kollisioner i en trång miljö. I detta examensarbete har ett program skrivits, som automatiskt genererar optimala lösningar för en klass av verkliga monteringsfall. Lösningen tar hänsyn till utformningen av monteringscellen och arrangerar cellen på bästa sätt, balanserar arbetsbelastningen, ordnar och tidsbestämmer uppgifter. Programmet använder sig av Google OR-Tools – ett öppet kodbibliotek för kombinatorisk optimering. Dessutom föreslås en skräddarsydd sökstrategi, som jämförs med Google OR-Tools inbyggda sökstrategi. Resultatet visar att den använda metoden är effektiv för problemtypen. Det tar ungefär 4 minuter att hitta den optimala lösningen och 32 minuter för att bevisa optimalitet. Dessutom visar resultatet att den anpassade sökstrategin konsekvent har en bra prestanda för olika problemfall. Dessutom är den anpassade strategin effektivare än den inbyggda sökstrategin i många fall.

Thesis (Ph. D.)--Industrial and Systems Engineering, Georgia Institute of Technology, 2006.
Joel Sokol, Committee Member ; Christiaan Paredis, Committee Member ; Gunter Sharp, Committee Member ; Marc Goetschalckx, Committee Chair ; Leon F. McGinnis, Committee Co-Chair. Includes bibliographical references.

Dans les dernières décennies, l'augmentation de la consommation des services de soins et la croissance de la population ont fait de l'élimination du gaspillage et l'amélioration continue de la productivité de plus en plus cruciale pour les hôpitaux. La productivité et l'efficacité d'un hôpital dépendent des conditions de travail des soignants qui sont influencés fortement par l'organisation des lieux de travail et des installations [Dares (2013)]. L’agencement des installations consiste à "déterminer l'organisation physique d'un système de production et de trouver l’arrangement le plus efficace de ‘n’ installations dans ‘n’ positions" [Singh et Sharma (2006)]. L’agencement des installations a un grand impact sur la productivité et l'efficacité du fonctionnement d'un hôpital. Etant conscient de ce besoin, le travail que nous présentons vise à trouver une solution à l’agencement des salles du Bloc Opératoire "le coeur de l'hôpital", ainsi que les salles annexes en proposant un outil intelligent que nous mettons à la disposition des maitres d’ouvrages pour optimiser leur conception du bloc opératoire. Les méthodes que nous avons explorées pour la réalisation de ce travail sont les méthodes exactes, les heuristiques, les métaheuristiques et les méthodes intelligentes, ce qui nous a permis de comparer les différentes approches afin de fournir la meilleure solution pour différents scénarios de problèmes. Nous présentons les contributions majeures de notre travail, à commencer par l'application de la programmation mathématique en nombres entiers mixtes (Mixed Integer Programming (MIP)) pour résoudre le problème d’agencement du bloc opératoire (Operating Theater Layout Problem (OTLP)) comme la première contribution scientifique. Ce travail considère trois structures différentes (multi-section, multi-étage et multi-rangé) dans deux types d'environnement différents, tout en optimisant deux fonctions objectifs différents. La combinaison de ces différentes composantes donne lieu à neuf modèles MIP pour résoudre l’OTLP pour lesquels une solution optimale a été atteinte pour des problèmes avec jusqu'à quarante salles. L'utilisation de Systèmes Multi-Agents (MAS) pour résoudre le problème d’agencement des installations est la deuxième contribution scientifique que nous présentons dans le cinquième chapitre. Dans la littérature, on retrouve un seul travail [Tarkesh et al., (2009)] ayant appliqué le MAS pour résoudre des problèmes de petites tailles, ce qui rend notre travail, le premier adoptant MAS pour répondre à la fois le FLP sous environnement statique et dynamique pour des problèmes de grande taille en utilisant un algorithme en trois étapes pour résoudre OTLP. La plate-forme multi-agents développée exploite les trois différents protocoles de communication d’agents, à savoir la coordination, la coopération et la négociation pour concevoir différentes architectures d’agents afin de faire face à l’OTLP statique et dynamique. La dernière contribution consistant en l'utilisation de l’optimisation par essaim de particules (Particle Swarm Optimization (PSO)) sous une représentation continue de l’espace de recherche pour résoudre le problème d’agencement multi-rangée est présentée dans le sixième chapitre. Puisque la PSO est généralement utilisé pour résoudre les problèmes d’affectation ou les FLP avec une représentation discrète, la formulation actuelle est parmi les rares travaux traitant la représentation continue du FLP. Nous avons conçu une nouvelle technique de codage des particules et des heuristiques appropriées pour générer des solutions initiales et pour effectuer la procédure de recherche locale. Une autre nouveauté est liée à l'application de la PSO à un problème de structure multi-rangé, qui n'a pas été abordé auparavant car à notre connaissance, les travaux avec la PSO ont formulé le FLP comme une structure d’une seule rangée ou dans le meilleur des scénarios, comme une structure à deux rangées
In the last decades, the important increasing consumption of health care and the growing of population make elimination of waste and continuous productivity improvement more and more critical for hospitals to provide their care services effectively and efficiently. The productivity and efficiency of a hospital depends on the caregivers working conditions, which are impacted greatly by the work place and the facilities organization [Dares (2013)]. Facilities planning “determines the physical organization of a production system and finding the most efficient arrangement of ‘n’ indivisible facilities in ‘n’ locations” [Singh & Sharma (2006)]. Thus, facilities planning has a great impact on the productivity and efficiency of running a hospital. Being aware of this need, the work we present aims to find a solution to facilities planning for the Operating Theater “the heart of hospital” by proposing an intelligent tool we make available to decision makers for optimizing their operating theater design. Our research work focuses on the use of operational research methods in order to find a solution for this optimization problem. Methods we explored for the realization of this work were variant, namely exact algorithm, heuristics, metaheuristics and intelligent methods, which allow us to compare different issues in order to provide the best solution to different scenarios of problems. Thus, in this dissertation we present the major contribution of our work, starting with the application of Mixed Integer Programming (MIP) to solve Operating Theater Layout Problem (OTLP) as the first scientific contribution. This work considers three different formulations (i.e. the multi-sections, the multi-floors and the multi-rows) in two different environment types (i.e. static and dynamic) while optimizing two different objective functions (i.e. to minimize the total traveling cost and to maximize the total adjacency rate). The combination of these different components gives rise to nine MIP models to solve the OTLP for which optimal solution was provided to problems with until forty facilities. These contributions are presented in the third and fourth chapters. The use of Multi-Agent System (MAS) to solve Facility Layout Problem (FLP) is the second scientific contribution we present in chapter five. In literature, only one work [Tarkesh et al., (2009)] applied the MAS to solve small sized problems, which makes our work the first one adopting MAS to address both the static and dynamic FLP for large sized problems using a novel algorithm running in three steps to solve OTLP. The developed multi-agent platform exploit the three different agents’ protocols of communication, namely coordination, cooperation and negotiation to conceive different agents’ architectures to deal with the static and dynamic OTLP. The last contribution consisting on the use of Particle Swarm Optimization (PSO) under continuous layout representation to solve multi-rows FLP is presented in chapter six. Since the PSO is generally used to solve assignment problems or discrete FLP, the actual formulation is among the few works dealing with the continuous one. This leads us to conceive a novel encoding technique and the appropriate heuristics to generate initial solutions and to perform the local search procedure. Another novelty is related to the application of PSO to a multi-rows layout problem, which was not addressed before. To the best of our knowledge, PSO works usually formulate the FLP as a single row or in the best of scenarios, as a double-rows problem

Thesis (Ed. D.)--Illinois State University, 1994.
Title from title page screen, viewed March 23, 2006. Dissertation Committee: Dent M. Rhodes (chair), James L. Bradford, Kenneth F. Jerich, Larry D. Kennedy. Includes bibliographical references (leaves 127-131) and abstract. Also available in print.

The facility layout problem (FLP) is one of the most important and challenging problems in both the operations research and industrial engineering research domains. In FLP research, the continuous-representation-based FLP can consider all possible all-rectangular department solutions. Given this flexibility, this representation has become the representation of-choice in FLP research. Much of this research is based on a methodology of mixed integer programming (MIP) models. However, these MIP-FLP models can only solve problems with a limited number of departments to optimality due to a large number of binary variables used in the models to prevent departments from overlapping. Our research centers around the sequence-pair representation, a concept that originated in the Very Large Scale Integration (VLSI) design literature. We show that an exhaustive search of the sequence-pair solution space will result in finding the optimal layout of the MIP-FLP and that every sequence-pair solution is binary-feasible in the MIP-FLP. Based on this fact, we propose a methodology that combines the sequence-pair and MIP-FLP model to efficiently solve large continuous-representation-based FLPs. Our heuristic approach searches the sequence-pair solution space and then use the sequence-pair representation to simplify and solve the MIPFLP model. Based on this methodology, we systematically study the different aspects of the FLP throughout this dissertation. As the first contribution of this dissertation, we present a genetic algorithm based heuristic, SEQUENCE, that combines the sequence-pair representation and the most recent MIPFLP model to solve the all-rectangular-department continuous-representation-based FLP. Numerical experiments based on different sized test problems from both the literature and industrial applications are provided and the solutions are compared with both the optimal solutions and the solutions from other heuristics to show the effectiveness and efficiency of our heuristic. For eleven data sets from the literature, we provide solutions better than those previously found. For the FLP with fixed departments, many sequence-pairs become infeasible with respect to the fixed department location and dimension restrictions. As our second contribution, to address this difficulty, we present a repair operator to filter the infeasible sequence-pairs with respect to the fixed departments. This repair operator is integrated into SEQUENCE to solve the FLP with fixed departments more efficiently. The effectiveness of combining SEQUENCE and the repair operator for solving the FLP with fixed departments is illustrated through a series of numerical experiments where the SEQUENCE solutions are compared with other heuristics' solutions. The third contribution of this dissertation is to formulate and solve the FLP with an existing aisle structure (FLPAL). In many industrial layout designs, the existing aisle structure must be taken into account. However, there is very little research that has been conducted in this area. We extend our research to further address the FLPAL. We first present an MIP model for the FLPAL (MIP-FLPAL) and run numerical experiments to test the performance of the MIP-FLPAL. These experiments illustrate that the MIP-FLPAL can only solve very limited sized FLPAL problems. Therefore, we present a genetic algorithm based heuristic, SEQUENCE-AL, to combine the sequence-pair representation and MIP-FLPAL to solve larger-sized FLPAL problems. Different sized data sets are solved by SEQUENCE-AL and the solutions are compared with both the optimal solutions and other heuristics' solutions to show the effectiveness of SEQUENCE-AL. The fourth contribution of this dissertation is to formulate and solve the FLP with non-rectangular-shaped departments. Most FLP research focuses on layout design with all rectangular-shaped departments, while in industry there are many FLP applications with non-rectangular-shaped departments. We extend our research to solve the FLP with nonrectangular-shaped departments. We first formulate the FLP with non-rectangular-shaped departments (FLPNR) to a MIP model (MIP-FLPNR), where each non-rectangular department is partitioned into rectangular-shaped sub-departments and the sub-departments from the same department are connected according to the department's orientation. The effect of different factors on the performance of the MIP-FLPNR is explored through a series of numerical tests, which also shows that MIP-FLPNR can only solve limited-sized FLPNR problems. To solve larger-sized FLPNR problems, we present a genetic algorithm based heuristic, SEQUENCE-NR, along with two repair operators based on the mathematical properties of the MIP-FLPNR to solve the larger-sized FLPNR. A series of numerical tests are conducted on SEQUENCE-NR to compare the SEQUENCE-NR solutions with both the optimal solutions and another heuristic's solutions to illustrate the effectiveness of SEQUENCE-NR. As the first systematic research study on a methodology that combines the sequence-pair representation and the MIP-based FLP, this dissertation addresses different types of continuous-representation based facility layout design problems: from block layout design with and without fixed departments to re-layout design with an existing aisle structure, and from layout design with all-rectangular-shaped departments to layout design with arbitrary non-rectangular-shaped departments. For each type of layout design problem, numerical experiments are conducted to illustrate the effectiveness of our specifically designed family of sequence-pair and MIP-based heuristics. As a result, better solutions than those previously found are provided for some widely used data sets from the literature and some new datasets based on both the literature and industrial applications are proposed for the first time. Furthermore, future research that continues to combine the sequence-pair representation and the MIP-FLP model to solve the FLP is also discussed, indicating the richness of this research domain.
Ph. D.

The k-sample data setting is one of the most common data settings used today. The null hypothesis that is most generally of interest for these methods is that the k-samples have the same location. Currently there are several procedures available for the individual who has data of this type. The most often used method is commonly called the ANOVA F-test. This test assumes that all of the underlying distributions are normal, with equal variances. Thus the only allowable difference in the distributions is a possible shift, under the alternative hypothesis. Under the null hypothesis, it is assumed that all k distributions are identical, not just equally located. Current nonparametric methods for the k-sample setting require a variety of restrictions on the distribution of the data. The most commonly used method is that due to Kruskal and Wallis (1952). The method, commonly called the Kruskal-Wallis test, does not assume that the data come from normal populations, though they must still be continuous, but maintains the requirement that the populations must be identical under the null, and may differ only by a possible shift under the alternative. In this work a new procedure is developed which is exactly distribution free when the distributions are equivalent and continuous under the null hypothesis, and simulations are used to study the properties of the test when the distributions are continuous and have the same medians under the null. The power of the statistic under alternatives is also studied. The test bears a resemblance to the two sample sign type tests, which will be pointed out as the development is shown.
Ph. D.

[EN] The Facilities Layout Problem in a industrial plant (FLP) pursues the good ordenation of the integrating elements (that in this work they will call themselves facilities, understan-ding those elements of the production system that they require space) of a production system and it contemplates, among other, geometric and economic aspects. The eco-nomic aspect has to do with the installation of the plant and with its operation while the geometric one is related with the architecture of the system. Under consideration of these aspects they are derived different formulations of the problem according to the geometric model adopted for represent the solution and according to the function to optimize that can include quantitative terms as installation costs and operation cost (manu-tención) and qualitative terms derived of the chart establishing relationship of activities from the met-hodology SLP. Certain tradition exists in the Educational Unit of Buildings and Architectu-re Industrial (at the moment U.D of Industrial Buldings), on the resolution of this FLP from diverse focuses, what there is origin that already from the years 90, myself, author of this thesis, as well as other partners, let us have implemented some computer applications of several types for the resolution of the same, based, by way of example, in genetic algo-rithms or in fuzzy logic. The last one goal was this one implemented with ACO ("Ant Co-lony Optimization") that this work shows. Anyway, this applications, often used in other works or even with educational ends, they have provided satisfactory results so much in the investigating scheduling as in the academic. At the beginning of the 2000, when the normative of Industrial Buldings Fire Proofing appears, when being starting from then of a preceptive normative in the greater part of industries of new installation, and the position that was continued in the real works was: in a first phase the elaboration of the layout, while in a second phase the application of the preceptive normative of fire proofing was demanded against fires to the layout obtained previously, with obligatory character so much in the industrial field, like in the subsidiary uses that aren't industrials, different from the main one. Any layout that it doesn't complete the fire proofing normative approaches in all the areas, be these industrial or not, it lacks legal validity and therefore it's not viable. In a third phase it is endowed of the thermal appropriate atmosphere, higroscopic, acous-tic and lighting to the obtained solution. In front of this reality, more and more commenda-ble starting from the appearance of the Technical Code of Buildings, that impels the per-formance designing and not in prescriptions, of the non convenience of unlying the design phases, we have started including the approach of the compartmentalization in the design like another objective in the quality of the final adopted solution, and therefore optimizable like any another. Hence in this work we have been carried out a proposal of compart-mentalization algorithm that works starting from the information and approaches that the normative of fires use, and we have also defined a proposal of objective function, as well as a series of parameters that allows to consider like it influences this compartmentaliza-tion in the flow of materials through the different facilities.
[ES] El problema de la distribución en planta de procesos industriales (FLP) persigue la ordenación óptima de los elementos (que en este trabajo se llamarán actividades, conceptuándose como aquellos elementos del sistema de producción que requieren espacio) de un sistema de producción y contempla, entre otros, aspectos geométricos y económicos. El aspecto económico tiene que ver con la instalación de la planta y con su operación mientras que el geométrico se relaciona con la arquitectura del sistema. De la consideración de estos aspectos se derivan diferentes formulaciones del problema según el modelo geométrico adoptado para representar la solución y según la función a optimizar, que puede incluir términos cuantitativos como costes de instalación y de operación (manutención) y términos cualitativos derivados de la tabla relacional de actividades establecida desde la metodología SLP. Existe cierta tradición en la Unidad Docente de Construcción y Arquitectura Industrial (actualmente U.D de Construcciones Industriales), sobre la resolución de este problema de distribución en planta desde diversos enfoques, lo que ha originado que ya desde los años 90, yo mismo, autor de esta Tesis Doctoral, así como otros compañeros, hayamos implementado algunas aplicaciones informáticas de varios tipos para la resolución del mismo, basadas, a modo de ejemplo, en algoritmos genéticos o en lógica borrosa. El último caso el de la aplicación informática que utiliza ACO ("Ant Colony Optimization") que se presenta en este trabajo. En cualquier caso, dichas aplicaciones, a menudo utilizadas en otras investigaciones o incluso con fines docentes, han proporcionado resultados satisfactorios tanto en el plano investigador como en el académico. A principios de los 2000, cuando aparece la normativa de Protección Contra Incendios en Establecimientos Industriales, al tratarse a partir de entonces de una normativa de obligado cumplimiento en la gran mayoría de actividades de nueva planta, y el planteamiento que se siguió al realizar los trabajos y proyectos sobre casos reales fue en una primera fase la elaboración de la distribución en planta, mientras que en una segunda fase se exigía la aplicación de la normativa de protección contra incendios a la distribución en planta obtenida con anterioridad, con carácter obligatorio tanto en el ámbito industrial, como en los usos subsidiaros no industriales diferentes del principal. Cualquier distribución en planta que no cumpla los criterios normativos en todas las zonas, sean éstas industriales o no, carece de validez legal y por tanto no es viable. En una tercera fase se dota del adecuado ambiente térmico, higroscópico, acústico y lumínico a la solución obtenida. Frente a esta realidad, cada vez más plausible a partir de la entrada en vigor del Código Técnico de la edificación, que impulsa el diseño basado en prestaciones y no en prescripciones, de la no conveniencia de desligar las fases de diseño, se ha comenzado por incluir el criterio de la sectorización en el diseño como un objetivo más mesurable en la calidad de la solución final adoptada, y por lo tanto optimizable como cualquier otro. Por ello en este trabajo se ha realizado una propuesta de algoritmo de sectorización, que funciona a partir de la información y criterios que las normativas de incendios utilizan, y se ha definido también una propuesta de función objetivo, así como una serie de parámetros que permiten considerar cómo influye esta sectorización en el trasiego de materiales (fundamentalmente flujos) a través de las distintas actividades.
[CAT] El problema de la distribució en planta de processos industrials (FLP) perseguix l'ordena-ció òptima dels elements (que en este treball es cridaran activitats, conceptuant-se com aquells elements del sistema de producció que requerixen espai) d'un sistema de pro-ducció i contempla, entre altres, aspectes geomètrics i econòmics. L'aspecte econòmic té a veure amb la instal·lació de la planta i amb la seua operació mentres que el geo-mètric es relaciona amb l'arquitectura del sistema. De la consideració d'estos aspectes es deriven diferents formulacions del problema segons el model geomètric adoptat per a representar la solució i segons la funció a optimitzar, que pot incloure termes quantitatius com a costos d'instal·lació i d'operació (manutenció) i termes qualitatius derivats de la taula relacional d'activitats establida des de la metodologia SLP. Hi ha una certa tradició en la Unitat Docent de Construcció i Arquitectura Industrial (actualment U.D de Cons-truccions Industrials) , sobre la resolució d'este problema de distribució en planta des de diversos enfocaments, la qual cosa ha originat que ja des dels anys 90, jo mateix, autor d'esta tesi, així com altres companys, hàgem implementat algunes aplicacions informàti-ques de diversos tipus per a la resolució del mateix, basades, a manera d'exemple, en algoritmes genètics o en lògica borrosa. L'últim cas el de l'aplicació informàtica que uti-litza ACO ("Ant Colony Optimization") que es presenta en este treball. En tot cas, les dites aplicacions, sovint utilitzades en altres investigacions o inclús amb fins docents, han pro-porcionat resultats satisfactoris tant en el pla investigador com en l'acadèmic. A principis dels 2000, quan apareix la normativa de Protecció Contra Incendis en Establiments In-dustrials, al tractar-se a partir de llavors d'una normativa de compliment obligatori en la gran majoria d'activitats de nova planta, i el plantejament que es va seguir en els treballs i projectes reials va ser en una primera fase l'elaboració de la distribució en planta, men-tres que en una segona fase s'exigia l'aplicació de la normativa de protecció contra in-cendis a la distribució en planta obtinguda amb anterioritat, amb caràcter obligatori tant en l'àmbit industrial, com en els usos subsidiar-vos no industrials diferents del principal. Qualsevol distribució en planta que no complisca els criteris normatius en totes les zones, siguen ést. En una tercera fase es dota de l'adequat ambient tèrmic, higroscòpic, acústic i lumínic a la solució obtinguda. Enfront d'esta realitat, cada vegada més plausible a partir de l'entrada en vigor del Codi Tècnic de l'Edificació, que impulsa el disseny basat en prestacions i no en prescripcions, de la no conveniència de deslligar les fases de disseny, s'ha començat per incloure el criteri de la sectorització en el disseny com un objectiu més mesurable en la qualitat de la solució final adoptada, i per tant optimizable com qualsevol altre. Per això en este treball s'ha realitzat una proposta d'algoritme de sectorització, que funciona a partir de la informació i criteris que les normatives d'incendis utilitzen, i s'ha definit també una proposta de funció objectiu, així com una sèrie de paràmetres que permeten considerar com influïx esta sectorització en el trasbals de materials (fonamen-talment fluxos) a través de les distintes activitats.
Jaén Gómez, PI. (2015). Algoritmos híbridos para la resolución del F.L.P. (Facility Layout Problem) basados en colonias de hormigas [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/59447
TESIS

In this thesis, the gate matrix layout problem in VLSI design is considered where the goal is to minimize the number of tracks required to layout a given circuit and a taxonomy of approaches to its solution is presented. An efficient hybrid heuristic is also proposed for this combinatorial optimization problem, which is based on the combination of probabilistic hill-climbing technique and greedy method. This heuristic is tested experimentally with respect to four existing algorithms. As test cases, five benchmark problems from the literature as well as randomly generated problem instances are considered. The experimental results show that the proposed hybrid algorithm, on the average, performs better than other heuristics in terms of the required computation time and/or the quality of solution. Due to the computation-intensive nature of the problem, an exact solution within reasonable time limits is impossible. So, it is difficult to judge the effectiveness of any heuristic in terms of the quality of solution (number of tracks required). A probabilistic model of the gate matrix layout problem that computes the expected number of tracks from the given input parameters, is useful to this respect. Such a probabilistic model is proposed in this thesis, and its performance is experimentally evaluated.

In this dissertation, we address three different combinatorial optimization problems (COPs), each of which has specific real-life applications. Owning to their specific nature, these problems are different from those discussed in the literature. For each of these problems, we present a mathematical programming formulation, analyze the problem to determine its useful, inherent structural properties, and develop an efficient methodology for its solution by exploiting these properties. The first problem that we address is the course timetabling problem encountered at Virginia Tech. The course timetabling problem for a university is a difficult problem and has been studied by many researchers over the years. As a result, a plethora of models and approaches have been reported in the literature. However, most of these studies have focused on applications pertaining to course scheduling for a single or at most few departments of a university. The sheer size of the university-wide timetabling problem that we address, involving thousands of courses to be scheduled in hundreds of classrooms in each semester, makes it a challenging problem. We employ an appropriate decomposition technique that relies on some inherent structural properties of the problem both during the modeling and algorithmic development phases. We show the superiority of the schedules generated by our methodology over those that are currently being used. Also, our methodology requires only a reasonable amount of computational time in solving this large-size problem. A facility layout problem involving arbitrary-shaped departments is the second problem that we investigate in this dissertation. We designate this problem as the arbitrary-shaped facility layout problem (ASFLP). The ASFLP deals with arranging a given set of departments (facilities, workstations, machines) within the confines of a given floor space, in order to optimize a desired metric, which invariably relates to the material handling cost. The topic of facility planning has been addressed rather extensively in the literature. However, a major limitation of most of the work reported in the literature is that they assume the shape of a department to be a rectangle (or even a square). The approach that relies on approximating an arbitrary-shaped department by a rectangle might result in an unattractive solution. The key research questions for the ASFLP are: (1) how to accurately model the arbitrary-shaped departments, and (2) how to effectively and efficiently determine the desired layout. We present a mixed-integer programming model that maintains the arbitrary shapes of the departments. We use a meta-heuristic to solve the large-size instances of the ASFLP in a reasonable amount of time. The third problem that we investigate is a supply chain scheduling problem. This problem involves two stages of a supply chain, specifically, a manufacturer and one or more customers. The key issue is to achieve an appropriate coordination between the production and distribution functions of the manufacturer so as to minimize the sum of the shipping and job tardiness costs. We, first, address a single customer problem, and then, extend our analysis to the case of multiple customers. For the single-customer problem, we present a polynomial-time algorithm to solve it to optimality. For the multiple-customer problem, we prove that this problem is NP-hard and solve it by appropriately decomposing it into subproblems, one of which is solvable in polynomial time. We propose a branch-and-bound-based methodology for this problem that exploits its structural properties. Results of an extensive computational experimentation are presented that show the following: (1) our algorithms are efficient to use and effective to implement; and (2) significant benefits accrue as a result of integrating the production and distribution functions.
Ph. D.

Lau Chun Ming.
Thesis (M.Phil.)--Chinese University of Hong Kong, 1997.
Includes bibliographical references (leaves 122-125).
Chapter Chapter 1: --- Introduction --- p.1
Chapter 1.1 --- Overview --- p.1
Chapter 1.2 --- Static Plant Layout Problem --- p.1
Chapter 1.3 --- Dynamic Plant Layout Problem --- p.3
Chapter 1.4 --- Example Problem of SPLP --- p.4
Chapter 1.5 --- Formulation of SPLP --- p.7
Chapter 1.6 --- Example Problem of DPLP --- p.8
Chapter 1.7 --- Mathematical Model of DPLP --- p.12
Chapter 1.8 --- Characteristics of the DPLP --- p.13
Chapter 1.9 --- Constrained Dynamic Plant Layout Problem (CDPLP) --- p.14
Chapter 1.10 --- Mathematical Model of CDPLP --- p.14
Chapter 1.11 --- Objective of the Research --- p.15
Chapter 1.12 --- Conclusion --- p.16
Chapter Chapter 2: --- Literature Review --- p.17
Chapter 2.1 --- Overview --- p.17
Chapter 2.2 --- Static Plant Layout Problem (SPLP) --- p.17
Chapter 2.2.1 --- The optimal algorithms
Chapter 2.2.2 --- The sub-optimal algorithms
Chapter 2.2.3 --- Construction algorithms
Chapter 2.2.4 --- Improvement algorithms
Chapter 2.3 --- Dynamic Plant Layout Problem (DPLP) --- p.21
Chapter 2.4 --- Conclusion: --- p.26
Chapter Chapter 3: --- Genetic Algorithms in DPLP --- p.27
Chapter 3.1 --- Introduction of Genetic Algorithms --- p.27
Chapter 3.2 --- Genetic Algorithms in DPLP --- p.28
Chapter 3.2.1 --- Encoding of a solution
Chapter 3.2.2 --- Fitness function
Chapter 3.2.3 --- Crossover operator
Chapter 3.2.4 --- Selection scheme
Chapter 3.2.5 --- Replacement and reproduction
Chapter 3.2.6 --- Mutation
Chapter 3.2.7 --- Initialization of parent pool
Chapter 3.2.8 --- Termination criterion
Chapter 3.3 --- Summary of the Proposed Method --- p.50
Chapter Chapter 4: --- Computational Result of GA in DPLP --- p.51
Chapter 4.1 --- Overview --- p.51
Chapter 4.2 --- Characteristics of the Testing Problems --- p.51
Chapter 4.3 --- Mathematical Model of DPLP for the Testing Problem --- p.52
Chapter 4.4 --- The Design of Experiment --- p.53
Chapter 4.4.1 --- The experiment
Chapter 4.4.2 --- Generating the initial layouts:
Chapter 4.5 --- Result: --- p.56
Chapter 4.6 --- Analysis of Results --- p.60
Chapter 4.6.1 --- 6department problems
Chapter 4.6.2 --- 15and 30 department problems
Chapter 4.7 --- Conclusion --- p.66
Chapter Chapter 5: --- Constrained Dynamic Plant Layout Problem --- p.68
Chapter 5.1 --- Overview --- p.68
Chapter 5.2 --- The Mathematical Model of CDPLP --- p.69
Chapter 5.3 --- Properties of CDPLP --- p.69
Chapter 5.4 --- The Proposed GA on CDPLP --- p.71
Chapter 5.4.1 --- Introduction
Chapter 5.4.2 --- Procedure
Chapter 5.4.3 --- Properties of dynamic programming under the dummy periods
Chapter 5.4.4 --- Properties of the proposed GA under the dummy periods
Chapter 5.4.5 --- The maximum number of iteration for the procedure
Chapter 5.5 --- Design of Experiment --- p.78
Chapter 5.6 --- Result of Experiment on CDPLP --- p.81
Chapter 5.7 --- Analysis of Results --- p.91
Chapter 5.7.1 --- Type 1 budget (self):
Chapter 5.7.2 --- The average cost of the test
Chapter 5.8 --- Conclusion: --- p.93
Chapter Chapter 6: --- Conclusion --- p.94
Appendix A: The Improved Implementation for Conway and Venkataramanan's GA --- p.96
Appendix B: Computational Result for CDPLP --- p.98
Bibliography --- p.122

碩士
元智大學
工業工程與管理學系
90
Abstract The facility layout problem is to optimize the relative location of the departments with the minimum cost of either material handling or interactive cost. The effective layout of the facilities is one of the keys to the success of the production system for the poor layout and design will cost more and deteriorate the operational efficiency. Past researches were mostly focused on the quantitative measures (e.g., material handling cost), while few were concerned about the qualitative measures (e.g., adjacent closeness). This purpose of this research was to study the facility layout problem based on the adjacency closeness measure. For the qualitative factor, this study focuses on the department closeness measure and utilize the space-filling curve to generate the layout. The proposed approach can help the designer with another choice other than the traditional cost based measures. The results show that this proposed model can obtain better solution in both Total Closeness Rating (TCR) and Weighted Closeness Rating (WCR) than the traditional approaches.

The single row layout problem (SRLP) is a specially structured instance of the classical facility layout problem, especially used in flexible manufacturing systems. The SRLP consists of finding the most efficient arrangement of a given number of machines along one side of the material handling path with the purpose of minimising the total weighted sum of distances among all machine pairs. To reflect real manufacturing situations, a minimum space (so-called clearances) between machines may be required by observing technological constraints, safety considerations and regulations. This thesis intends to outline the different concepts of clearances used in literature and analyse their effects on modelling and solution approaches for the SRLP. In particular the special characteristics of sequence-dependent, asymmetric clearances are discussed and finally extended to large size clearances (machine-spanning clearances). For this, adjusted and novel model formulations and solution approaches are presented. Furthermore, a comprehensive survey of articles published in this research area since 2000 is provided which identify recent developments and emerging trends in SRLP.

碩士
國立交通大學
工業工程研究所
83
The result of facility layout will influence the performance of production system and is the key factor of deciding production cost. This paper presents a multi-objective facility layout model for combining quantitative factor (material handling cost) and qualitative factor (closeness rating). In this model, closeness rating is weighted by a cost parameter in order to reduce the influence of difference between two objective functions, and let the quality of individual objective be close each other. During the programming procedure, consider changes in production level, this is "flexibility" of facility layout. In this paper, we use lost cost to measure the flexibility of a layout. The lower the lost cost is, the more flexible the layout is. Finally, this paper presents a two-phase algorithm to solve the flexible facility layout problem. In phase one, CRAFT is ployed to obtained the suboptimal layout for each period. Using these suboptimal layouts, the lost cost of each period can be caculated. In phase two, the most flexible layout during planning horizon can obtained by using simulated annealing algorithm.

The continuous facility layout problem consists of arranging a set of facilities so that no pair overlaps and the total sum of the pairwise connection costs (proportional to the center-to-center rectilinear distance) is minimized. This thesis presents a completely mixed integer semidefinite programming (MISDP) model for the continuous facility layout problem. To begin we describe the problem in detail; discuss the conditions required for a feasible layout; and define quaternary variables. These variables are the basis of the MISDP model. We prove that the model is an exact formulation and a distinction is made between the constraints that semidefinite programming (SDP) optimization software can solve and those that must be relaxed. The latter are called exactness constraints and three possible exactness constraints are shown to be equivalent. The main contribution of this thesis is the theoretical development of a MISDP model that is based on quaternary, as oppose to binary, variables; nevertheless preliminary computational results will be presented for problems with 5 to 20 facilities. The optimal solution is found for problems with 5 and 6 facilities, confirming the validity of the model; and the potential of the model is revealed as a new upper bound is found for an 11-facility problem.

碩士
朝陽大學
營建工程系碩士班
88
Construction site engineers have to face problems of allocating facilities to proper locations, which could maximize the productivity of construction sites. This kind of problems has not been easy to solve because the potential solution space usually is large. Genetic algorithms (GAs) are searching mechanisms based on nature selection, survival of the fittest, and theories of genes. GAs have proved to be efficient for solving large-scale optimization problems. A new genetic algorithm to improve efficiency in generating solutions for facility layout problems is developed in this research. The results show that the new algorithm can find the optimal solution efficiently. In addition, a user-friendly program based on the MicrosoftÒ Excel and VBA is developed, which make the results more applicable to facility layout problems.

碩士
國立臺北科技大學
工業工程與管理研究所
99
Facility Layout combines resource include human、material and equipment to be the most efficient planning, and balance other installation to transform well use for company in improve organize functions and development of long-term effectiveness. A good layout plan can improve the productivity and efficiency of information delivery; a bad one can obstruct the product process or waste superfluous material handling, increase the company operation cost. In reality, the academe and the industry all input considerable resources for FLP. Advanced scholars develop GA、SA、ACO and PSO to solve FLP. Recently, Harmony Search algorithm get the well results in solve problem in many fields, even better than GA. This research develops placement to place facility without partition and respectively employ Harmony Search algorithm (HS) to find out the best layout with the minimum material handing cost. Then, compare results with existing algorithm.

碩士
中原大學
工業工程研究所
102
Abstract Traditional facility layout problem assumes that all of the parameter are known. However in the real world, parameter such as demand of the product would always keep changing; this in result, will affect the production demand. Stochastic facility layout problem have the advantage, such that it can adapt over time subjected to the fluctuations in demand and in results would affect the production demand as well. To create more similar environment to real world scenario, the proposed study would use the stochastic facility layout problem to minimize material handling costs and wastes. Since, facility layout problem is NP-Hard problem we would use meta-heuristic to solve and find the best possible solution. The more recently meta-heuristic, Bat Algorithm (Yang, 2010) is proven to be faster and more efficient on solving benchmark functions (De Jong's, Schwefel's, etc) compared to the previous meta-heuristics. However, no research has been done on implementing bat algorithm to the facility layout problem. the proposed study, proposes a new method on implementing bat algorithm to solve facility layout problem dealing with uncertainty. As a benchmark, Simulated Annealing (SA) algorithm is used as a comparison with the new proposed meta-heuristic. The findings show that Bat Algorithm is proven to be faster and more efficient compare to the SA algorithm. Keyword: Stochastic facility layout problem, Uncertainty, Risk, Bat Algorithm, Simulated Annealing Algorithm

碩士
立德管理學院
應用資訊研究所
95
The facility layout problem is a part of the application in the artificial intelligence. It is belong to the combinatorial optimization and quadratic assignment problem. For many artificial intelligence tools, the tabu search algorithm is widely applied to a lot of combinatorial optimization problems. In this research, an improved tabu search algorithm is developed to solve a NP-complete problem in the facility layout problem. The approach on the two facilities layout problems is examined. The first one is a construction site layout problem, and the second one is a hospital facility layout problem. In order to get better layout result, this research has tried the different setting in this algorithm by altering the values of parameters. This research can provide a good algorithm to solve the quadratic assignment problem in facility layout arrangement.

碩士
南台科技大學
工業管理研究所
97
Facility layout, the appropriateness of the decision of the entire production system of cost and efficiency, because a good layout mode will help to improve the efficiency of production systems and process on the manufacture, opposite poor layout mode will greatly reduce the efficiency of production. In the traditional solving facility layout mode, most are select one model to solve of qualitative or quantitative model. as a result of people who use quantitative model believe that the relationship between adjacent facilities, it is difficult to quantify the reasonable. So it is not considered in a model. But this kind of planning, often resulting facilities adjacent but that should not adjacent. That will make the manufacturing process in the troubled and reduce production efficiency. In the qualitative model also assumes that all factors of the facility layout is used to represent closeness rating. To make the planning are subjective. Therefore the study will thank about qualitative approach and quantitative approach on the same time. To become a multiple objective optimization question. There are many algorithms that solve a multiple objective optimization question have been published. Genetic Algorithm operations process is Parallel Search and many chromosomes are worked equal to a group of temporary solutions at the same time in search. That can make solving more stable quality, and in solving the optimization problem, there is no limit too much of mathematics. All discrete, continuous and mixed of space that limitations and its objectives is linear or nonlinear operations can be solved. So this study will use the genetic algorithm to solve the facility layout problems, and considering two different attributes of the target and solving the final pareto optimal set. Using genetic algorithm of the special characteristic, save a lot of time, in order to make pursuant to decision by leaders and picked out a more appropriate solution for the final implementation to solve the multi-objective optimization problem of facility layout.

The facility layout problem is modelled as a cycle decomposition process in which the maximum-weight clique and travelling salesman problems are utilized to extract cycles from the graph adjacency matrix. The space between cycles is triangulated so the graph is maximally planar. The adjacency graph is then systematically developed into a block plan layout. With use of the maximum-weight clique algorithm, the procedure addresses layout problems that are not 100% dense. Many examples are utilized to demonstrate the flexibility of the algorithm and the resulting adjacency graph and block plan layout drawings. The Steiner Circulation Network solution derived from an adjacency graph solution and its dual graph, provides a minimum cost system of hallways and connecting links for the material handling system. Using the flows between activities and departments in a layout problem, the circulation network provides the necessary link between the steps of finding the adjacency graph solution and finding useful block plan layout. A case study demonstrates how the solution for the layout and its material handling system can be integrated. Computational results up to size n = 100 are presented along with a comparative study with a competitive algorithm.

博士
元智大學
工業工程與管理學系
91
A Study of Facility Layout Problem by Genetic Algorithm Student : Ming-Jaan Wang Advisor : Dr. Michael H. Hu Institute of Industrial Engineering and Management Yuan-Ze University ABSTRACT Minimal material handling cost (MHC) achievement is one of the critical objectives in facilities layout problems for layout designers. However, solving the larger departments of facilities layout problem accompanying with the optimal MHC is time-consuming or even infeasible. Therefore, many heuristic algorithms such as simulated annealing (SA), tabu search (TA), and genetic algorithm (GA) were developed to find out near-optimal solutions for MHC. This study used genetic algorithm and a rule-based expert system to implement and create space filling curve (SFC), for achieving the optimal solution of the discrete facility layout problem. Concerning the equal area department problems, the objective function is mainly according to the measurement of material flow factor cost (MFFC). However, the objective function for unequal area department problem in this study is a multiple criteria, involving MFFC, shape ratio factor (SRF), and area utilization factor (AUF) to reach minimal total layout cost (TLC). Then, a method of modified the irregular-shape departments to regular-shape ones and eliminate the redundant areas based on the principle of 100% area utilization is proposed. The experimental results show that the proposed approach is much more feasible for dealing with the facilities layout problems and better than existed results. Keyword: Genetic Algorithm, Space Filling Curve, Material Flow Factor Cost, Shape Ratio Factor, Area Utilization Factor, Total Layout Cost

碩士
國立成功大學
工學院工程管理專班
97
Solar energy industry has been developed rapidly in recent years. They are required in the production technology to the way (Turn-key solution) that copy the same experience rapidly, so at this stage for the industry with high homogeneity. If we want to enhance our competitiveness nothing is better than from the manufacturing process is upgraded and lower production costs are reduced effectively .It is also base on plant facilities. Plant facilities layout (Layout) is always for the performance of manufacturing systems have a significant impact. The general layout of the facilities solutions are measured the quality of design on transport distance, these methods can not be considered effectively on multi-objective decision-making problem, so cannot ensure the problem solution quality on multi-objective. From the practical point of view, the plant layout problem in essence is a need to emphasize communication and co-ordination and how to integrate the views of the majority of the multi-objective decision-making problems, the majority of literature are almost emphasis on solution method and rarely on the group decision-making process give a clear explain. Therefore, how to combine effectively the group decision-making structure and logic to find an easy application and suitability methods for thin-film solar industry is the key point of this paper. This paper combined with a Systematic Layout Planning(SLP)and the Analytic Hierarchy Process(AHP), used on the central spine layout to solve the facilities layout design problem for thin-film solar industry. First, by the SLP steps to do and use from - to chart to achieve transport cost for quantitative indicators; to operate and develop relationships to the working data. The working data are combine the expert suggestions and join the actual constraints to gain a number of alternatives and then by the Check List to confirm and find three better alternatives. Finally, to draw up the decision-making objectives. Then use AHP method to calculate of relative weight and consistency to estimate the best layout and carry out sensitivity analysis. The results show this method practicality and applicability for thin-film solar industries application of facility layout, it is the value of paper-based.