Relevant bibliographies by topics / Initial solution heuristic

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Initial solution heuristic'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Initial solution heuristic"

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Ursani, Ziauddin, and Ahsan Ahmad Ursani. "Augmented tour construction heuristics for the travelling salesman problem." International Journal of Industrial Optimization 4, no. 2 (2023): 131–44. http://dx.doi.org/10.12928/ijio.v4i2.7875.

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Tour construction heuristics serve as fundamental techniques in optimizing the routes of a traveling salesman. These heuristics remain significant as foundational methods for generating initial solutions to the Traveling Salesman Problem (TSP), facilitating subsequent applications of tour improvement heuristics. These heuristics effectively comprise the iterative application of city node selection and insertion. However, thus far, no attempts have been made to enhance the basic structure of tour construction heuristics to bring a better initial solution for the advanced heuristics. This study
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Saksuriya, Payakorn, and Chulin Likasiri. "Hybrid Heuristic for Vehicle Routing Problem with Time Windows and Compatibility Constraints in Home Healthcare System." Applied Sciences 12, no. 13 (2022): 6486. http://dx.doi.org/10.3390/app12136486.

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This work involves a heuristic for solving vehicle routing problems with time windows (VRPTW) with general compatibility-matching between customer/patient and server/caretaker constraints to capture the nature of systems such as caretakers’ home visiting systems or home healthcare (HHC) systems. Since any variation of VRPTW is more complicated than regular VRP, a specific, custom-made heuristic is needed to solve the problem. The heuristic proposed in this work is an efficient hybrid of a novice Local Search (LS), Ruin and Recreate procedure (R&R) and Particle Swarm Optimization (PSO). The
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Seipp, Jendrik, Florian Pommerening, and Malte Helmert. "New Optimization Functions for Potential Heuristics." Proceedings of the International Conference on Automated Planning and Scheduling 25 (April 8, 2015): 193–201. http://dx.doi.org/10.1609/icaps.v25i1.13714.

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Potential heuristics, recently introduced by Pommerening et al., characterize admissible and consistent heuristics for classical planning as a set of declarative constraints. Every feasible solution for these constraints defines an admissible heuristic, and we can obtain heuristics that optimize certain criteria such as informativeness by specifying suitable objective functions. The original paper only considered one such objective function: maximizing the heuristic value of the initial state. In this paper, we explore objectives that attempt to maximize heuristic estimates for all states (rea
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Jardón, Edgar, Marcelo Romero, and José-Raymundo Marcial-Romero. "Application of Optimization Algorithms in Voter Service Module Allocation." Information 16, no. 6 (2025): 506. https://doi.org/10.3390/info16060506.

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Allocation models are essential tools for optimally distributing client requests across multiple services under defined restrictions and objective functions. This study evaluates several heuristics to address an allocation problem involving young individuals reaching voting age. A five-step methodology was implemented: defining variables, executing heuristics, compiling results, evaluating outcomes, and selecting the most effective heuristic. Using experimental data from the Mexican National Electoral Institute (INE), the study focuses on 88,107 individuals aged 17–18 in the 16 municipalities
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Iqbal, Zahid, Rafia Ilyas, Huah Yong Chan, and Naveed Ahmed. "Effective Solution of University Course Timetabling using Particle Swarm Optimizer based Hyper Heuristic approach." Baghdad Science Journal 18, no. 4(Suppl.) (2021): 1465. http://dx.doi.org/10.21123/bsj.2021.18.4(suppl.).1465.

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The university course timetable problem (UCTP) is typically a combinatorial optimization problem. Manually achieving a useful timetable requires many days of effort, and the results are still unsatisfactory. unsatisfactory. Various states of art methods (heuristic, meta-heuristic) are used to satisfactorily solve UCTP. However, these approaches typically represent the instance-specific solutions. The hyper-heuristic framework adequately addresses this complex problem. This research proposed Particle Swarm Optimizer-based Hyper Heuristic (HH PSO) to solve UCTP efficiently. PSO is used as a high
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Castro, Eduardo Meca. "Two Neighbourhood-based Approaches for the Set Covering Problem." U.Porto Journal of Engineering 5, no. 1 (2019): 1–15. http://dx.doi.org/10.24840/2183-6493_005.001_0001.

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The Set Covering Problem is a well-known NP-complete problem which we address in this work. Due to its combinatorial nature heuristic methods, namely neighbourhood-based meta-heuristics, were used.Based on the well-known algorithms GRASP, Simulated Annealing and Variable Neighbourhood Descend, along with a constructive heuristic based on a dynamic dispatching rule to generate initial feasible solutions, two approaches to the problem were formulated. The performance of both methods was assessed in 42 instances of the problem. Our best approach has an average deviation from the best-known soluti
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Wang, Lingya, and Dean S. Oliver. "Efficient Optimization of Well-Drilling Sequence with Learned Heuristics." SPE Journal 24, no. 05 (2019): 2111–34. http://dx.doi.org/10.2118/195640-pa.

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Summary When preparing a field–development plan, the forecast value of the development can be sensitive to the order in which the wells are drilled. Determining the optimal drilling sequence generally requires many simulation runs. In this paper, we formulate the sequential decision problem of a drilling schedule as one of finding a path in a decision tree that is most likely to generate the highest net present value (NPV). A nonparametric online–learning methodology is developed to efficiently compute the sequence of drilling wells that is optimal or near optimal. The main ideas behind the ap
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Li, Bing, Xinyu Yang, and Hua Xuan. "A Hybrid Simulated Annealing Heuristic for Multistage Heterogeneous Fleet Scheduling with Fleet Sizing Decisions." Journal of Advanced Transportation 2019 (January 10, 2019): 1–19. http://dx.doi.org/10.1155/2019/5364201.

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This paper deals with multistage heterogeneous fleet scheduling with fleet sizing decisions (MHFS-FSD). This MHFS-FSD attempts to integrate vehicles allocation and fleet sizing decisions considering the vehicle routing of multiple vehicle types. The problem is formulated as mixed integer programming model. The matrix formulation denoting vehicle allocation scheme is explored according to the characteristic of this problem. Generating vehicle allocation scheme with greedy heuristic procedure (VA-GHP) as initial solution of problem is presented. The USP-IVA method to update the initial solution
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John Oyewole, Gbeminiyi, and Olufemi Adetunji. "A HYBRID ALGORITHM TO SOLVE THE FIXED CHARGE SOLID LOCATION AND TRANSPORTATION PROBLEM." Engineering Heritage Journal 5, no. 1 (2021): 01–11. http://dx.doi.org/10.26480/gwk.01.2021.01.11.

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In this paper, we propose a Hybrid Algorithm (HA) to solve the Fixed Charge Solid Location and Transportation problem (FCSLTP). The FCSLTP considers the cost of facility location and route fixed costs during transportation planning or load consolidation. The HA integrates two heuristics into the Genetic Algorithm framework to solve the FCSLTP. Genetic operations are used to select the best combination of facility locations while a greedy heuristic which uses some cost relaxations are used for the initial load allocation. An improvement heuristic, a modified stepping stone method, is then used
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Yang, Jie, and Yangsheng Jiang. "Application of Modified NSGA-II to the Transit Network Design Problem." Journal of Advanced Transportation 2020 (August 1, 2020): 1–24. http://dx.doi.org/10.1155/2020/3753601.

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The transit network design problem involves determining a certain number of routes to operate in an urban area to balance the costs of the passengers and the operator. In this paper, we simultaneously determine the route structure of each route and the number of routes in the final solution. A novel initial route set generation algorithm and a route set size alternating heuristic are embedded into a nondominated sorting genetic algorithm-II- (NSGA-II-) based solution framework to produce the approximate Pareto front. The initial route set generation algorithm aims to generate high-quality init
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Dissertations / Theses on the topic "Initial solution heuristic"

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Joubert, Johannes Wilhelm. "An initial solution heuristic for the vehicle routing and scheduling problem." Diss., 2004. http://hdl.handle.net/2263/27582.

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South Africa provides a fascinating interface between the developed and the developing world and poses a multitude of opportunities for enhancing the sustainable development of local cities. The concept of City Logistics is concerned with the mobility of cities, and entails the process of optimizing urban logistics activities by considering the social, environmental, economic, financial, and energy impacts of urban freight movement. Vehicle routing and scheduling has the potential to address a number of these key focus areas. Applying optimization to vehicle routing and scheduling results in a
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Book chapters on the topic "Initial solution heuristic"

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Faia, Ricardo, Tiago Pinto, and Zita Vale. "Initial Solution Heuristic for Portfolio Optimization of Electricity Markets Participation." In Communications in Computer and Information Science. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60285-1_11.

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Sapkal, Sagar, and Dipak Laha. "Comparison of Initial Solutions of Heuristics for No-wait Flow Shop Scheduling." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25734-6_44.

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King, Jacobus, and Jan van Vuuren. "A Recycling Heuristic Capable of Generating Initial Solutions for Use in Vehicle Routing Metaheuristics." In AIRO Springer Series. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-47686-0_11.

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Wang, Yunlong, Pengxiang Zhang, Yujie Gu, Xin Zhang, Chaoguang Jin, and Ming Chen. "Research of Ship Nesting Based on Maximum Residual Rectangle Strategy Integrated Improved Genetic Algorithm." In Advances in Transdisciplinary Engineering. IOS Press, 2024. http://dx.doi.org/10.3233/atde231141.

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In this paper, a maximum residual rectangle genetic (MRRG) algorithm based on multi-heuristic strategies is proposed, which combines the advantages of heuristic algorithm and intelligent optimization algorithm to improve the material utilization and stability of the solution. In this method, the optimal local solution is obtained by constructing the maximum residual rectangle (MRR) algorithm based on the heuristic algorithm firstly, and the free rectangle area table update method of MRR algorithm is put forward. Secondly, in order to further improve the diversity of solutions, five heuristic s
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Hammouri Abdelaziz I. and Abdullah Salwani. "Biogeography-Based Optimisation For Data Clustering." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2014. https://doi.org/10.3233/978-1-61499-434-3-951.

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Clustering is an important data analysis and data mining tool that is used in many fields and applications, which aims to find a homogeneous sets of objects based on the degree of similarity and dissimilarity of their attributes. One of the most popular techniques in data clustering is K-means, which is a simple, fast and efficient method that has been applied successfully in many fields. However, K-means has its own drawbacks like highly dependence on the initial solution and can easily trapped into local optima. In this paper, we investigate the behaviour of the newly created meta-heuristic
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Sahin, Yusuf, Erdal Aydemir, Kenan Karagul, Sezai Tokat, and Burhan Oran. "Metaheuristics Approaches for the Travelling Salesman Problem on a Spherical Surface." In Interdisciplinary Perspectives on Operations Management and Service Evaluation. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-5442-5.ch005.

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Traveling salesman problem in which all the vertices are assumed to be on a spherical surface is a special case of the conventional travelling salesman problem. There are exact and approximate algorithms for the travelling salesman problem. As the solution time is a performance parameter in most real-time applications, approximate algorithms always have an important area of research for both researchers and engineers. In this chapter, approximate algorithms based on heuristic methods are considered for the travelling salesman problem on the sphere. Firstly, 28 test instances were newly generat
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Ye, Xugang, Shih-Ping Han, and Anhua Lin. "A Note on the Connection Between the Primal-Dual and the A* Algorithm." In Innovations in Information Systems for Business Functionality and Operations Management. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-4666-0933-4.ch010.

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The primal-dual algorithm for linear programming is very effective for solving network flow problems. For the method to work, an initial feasible solution to the dual is required. In this article, we show that, for the shortest path problem in a positively weighted graph equipped with a consistent heuristic function, the primal-dual algorithm will become the well-known A* algorithm if a special initial feasible solution to the dual is chosen. We also show how the improvements of the dual objective are related to the A* iterations.
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Garcia, Ernesto Liñán, Carlos Gonzalez-Flores, and Linda Crystal Cruz-Villegas. "Hybrid Multi-Annealing Simulated Annealing Applied to Vehicle Routing Problem." In Handbook of Research on Military, Aeronautical, and Maritime Logistics and Operations. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-9779-9.ch018.

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In this chapter, a hybrid meta-heuristic algorithm is proposed, which is based on simulated annealing in order to solve the Vehicle Routing Problem (VRP) with stochastic demands. The proposed algorithm has several annealing phases, which are named Simulated Multi-annealing (SMA). This algorithm is combined with the Clarke and Wright saving algorithm (CW). This last algorithm was placed inside the Metropolis Cycle of Simulated Multi-annealing algorithm. The hybrid algorithm is applied to obtain optimal routes for a cleaning distribution company. The initial solution of VRP is generated by the C
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D'Haese, C. M. F., M. Putti, C. Paniconi, N. E. C. Verhoest, and F. P. De Troch. "Assessment of initial solution estimates and adaptive vs. heuristic time stepping for variably saturated flow." In Computational Methods in Water Resources: Volume 1. Elsevier, 2004. http://dx.doi.org/10.1016/s0167-5648(04)80080-7.

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K., Lakshmi, Karthikeyani Visalakshi N., Shanthi S., and Parvathavarthini S. "Clustering Mixed Datasets Using K-Prototype Algorithm Based on Crow-Search Optimization." In Developments and Trends in Intelligent Technologies and Smart Systems. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-3686-4.ch010.

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Data mining techniques are useful to discover the interesting knowledge from the large amount of data objects. Clustering is one of the data mining techniques for knowledge discovery and it is the unsupervised learning method and it analyses the data objects without knowing class labels. The k-prototype is the most widely-used partitional clustering algorithm for clustering the data objects with mixed numeric and categorical type of data. This algorithm provides the local optimum solution due to its selection of initial prototypes randomly. Recently, there are number of optimization algorithms
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Conference papers on the topic "Initial solution heuristic"

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Lu, Yunfeng. "A two-stage heuristic algorithm for high-quality initial solution generation in MTVRPTW." In 8th International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023), edited by Said Easa and Wei Wei. SPIE, 2023. http://dx.doi.org/10.1117/12.2689564.

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Trevizan, Felipe, Sylvie Thiebaux, Pedro Santana, and Brian Williams. "I-dual: Solving Constrained SSPs via Heuristic Search in the Dual Space." In Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/701.

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We consider the problem of generating optimal stochastic policies for Constrained Stochastic Shortest Path problems, which are a natural model for planning under uncertainty for resource-bounded agents with multiple competing objectives. While unconstrained SSPs enjoy a multitude of efficient heuristic search solution methods with the ability to focus on promising areas reachable from the initial state, the state of the art for constrained SSPs revolves around linear and dynamic programming algorithms which explore the entire state space. In this paper, we present i-dual, the first heuristic s
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Eftekharian, Ata A., and Horea T. Ilies¸. "Shape and Topology Optimization With Medial Zones." In ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/detc2011-48363.

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Shape optimization (with topological changes) has become a de facto standard approach for synthesizing new designs. Current approaches heavily rely on voxelized modifications of the initial domain, followed by heuristic reconstruction procedures that result in a detailed shape design. The initial domain is almost always conservatively estimated so that the design space spans a sufficiently large set of possible solutions. We propose a novel approach to shape optimization that exploits the geometric and topologic properties of medial zones and a new shape modification paradigm to synthesize sha
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Sousa, T., H. Morais, R. Castro, and Z. Vale. "A new heuristic providing an effective initial solution for a simulated annealing approach to energy resource scheduling in smart grids." In 2014 IEEE Symposium on Computational Intelligence Applications in Smart Grid (CIASG). IEEE, 2014. http://dx.doi.org/10.1109/ciasg.2014.7011563.

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Arotaritei, Dragos, Mihai Ilea, Trinca Carmen lucia, and Andrei Gheorghita. "A PROPOSAL FOR ISOTHERMAL MODEL SELECTION, A HEURISTIC APPROACH." In eLSE 2021. ADL Romania, 2021. http://dx.doi.org/10.12753/2066-026x-21-173.

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There are many mathematical models for sorption isotherms, with some practically application in the food chemistry. In this case, an isotherm describes a relationship (linear or nonlinear) between moisture content and water activity in a certain type of food. The hysteresis for a typical food product is taken into account with educational objective: a better understanding of the sorption process. Depending of the food chemical composition, the relationship between water activity and water content can be simple of very complex, a large number of models having been proposed to cover a large vari
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Hart, P. K., and J. Rodriguez. "A Dual-Purpose KBES for Preliminary Structural Design." In ASME 1989 Design Technical Conferences. American Society of Mechanical Engineers, 1989. http://dx.doi.org/10.1115/detc1989-0092.

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Abstract A prototype expert system for automatic preliminary shape synthesis is being developed. The purpose of this system is to generate preliminary designs which can be used either for basic engineering or as an initial solution in an optimization scheme. The developed prototype intends to emulate the conceptual-design/preliminary-redesign phases in the design process. Both phases have been modularized and developed under adequate computational shells. Modules requiring heuristic support are implemented in a LISP/KEE™ environment, the ones being computer-intensive are in C subroutines. Heur
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Rao, J. R. J., and P. Y. Papalambros. "Implementation of Semi-Heuristic Reasoning for Boundedness Analysis of Design Optimization Models." In ASME 1987 Design Technology Conferences. American Society of Mechanical Engineers, 1987. http://dx.doi.org/10.1115/detc1987-0008.

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Abstract A production system performing global boundedness analysis of optimal design models has been implemented in the OPS5 programming environment. The system receives as input an initial model monotonicity table and derives global facts about boundedness and constraint activity using monotonicity principles. Additional facts may be discovered by heuristic search of implicit elimination sequences that examine boundedness of reduced models with active constraints eliminated. The global facts generated automatically by this reasoning system can be used either for a global solution, or for a c
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De Freitas, Elthon Manhas, Karina Valdivia Delgado, and Valdinei Freire. "Risk Sensitive Probabilistic Planning with ILAO* and Exponential Utility Function." In XV Encontro Nacional de Inteligência Artificial e Computacional. Sociedade Brasileira de Computação - SBC, 2018. http://dx.doi.org/10.5753/eniac.2018.4434.

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Markov Decision Process (MDP) has been used very efficiently to solve sequential decision-making problems. However, there are problems in which dealing with the risks of the environment to obtain a reliable result is more important than minimizing the total expected cost. MDPs that deal with this type of problem are called risk-sensitive Markov decision processes (RSMDP). In this paper we propose an efficient heuristic search algorithm that allows to obtain a solution by evaluating only the relevant states to reach the goal states starting from an initial state.
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Namala, Prannoy, Arjun Vaidya, and Jeffrey W. Herrmann. "Data Driven Metareasoning for Defending a Perimeter Against Cooperative Intrusion." In ASME 2024 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2024. http://dx.doi.org/10.1115/detc2024-143159.

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Abstract Perimeter defense problem is a type of differential game, where a team of attacker agents try to score by intruding a perimeter region while a team of defenders try to defend the perimeter by intercepting the attackers. There are many approaches to the multi-agent perimeter defense problem proposed over the last decade with varying assumptions. However, even the most general approach cannot generate an optimal solution for every situation. In some situations, a heuristic-based solution might work better than a complex one. Choosing the right solution will help in higher performance an
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Felipe Borreiro Sanches, Mauricio Iwama Takano, and Marcelo Seido Nagano. "COMPARISON AMONG HEURISTIC METHODS TO PROVIDE AN INITIAL SOLUTION FOR A BRANCH-AND-BOUND ALGORITHM TO MINIMIZE THE MAKESPAN IN A FLOW SHOP WITH BLOCKING ENVIRONMENT." In 23rd ABCM International Congress of Mechanical Engineering. ABCM Brazilian Society of Mechanical Sciences and Engineering, 2015. http://dx.doi.org/10.20906/cps/cob-2015-1297.

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