Journal articles: 'Resource constraint project scheduling'

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Gao, Yan, Xin Zhang, and Jian Zhong Xu. "An Improved Production Scheduling Algorithm Based on Resource Constraints." Applied Mechanics and Materials 455 (November 2013): 619–24. http://dx.doi.org/10.4028/www.scientific.net/amm.455.619.

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For resource-constrained project scheduling problems, with aircraft assembly as its background, we established its mathematics model as constraint satisfaction problem. An improved critical path scheduling algorithm is proposed, considering the constraints of precedence relations, resource constraints and space constraints, through the two stages of planning, reaching for aircraft assembly task scheduling optimization objectives. Through the given numerical example results show that, when the objective consists in minimizing the project duration, the algorithm has better performance.

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Chen, Junjie, Shurong Tong, Hongmei Xie, Yafei Nie, and Jingwen Zhang. "Model and Algorithm for Human Resource-Constrained R&D Program Scheduling Optimization." Discrete Dynamics in Nature and Society 2019 (April 3, 2019): 1–13. http://dx.doi.org/10.1155/2019/2320632.

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In resource-constrained project scheduling problems, renewable resources can be expanded into human resources with competency differences. A flexible resource-constrained project scheduling problem with competency differences is proposed, which is a practical extension close to Research and Development (R&D) program management, from the traditional multimode resource-constrained project scheduling problem. A parameter and estimation formula to measure staff competency is presented, and a mixed-integer programming model is established for the problem. The single-objective optimization problems of optimal duration and optimal cost are solved sequentially according to the biobjective importance. To solve the model, according to the assumptions and constraints of the model, the initial network diagram of multiple projects is determined, the enumeration algorithm satisfying constraint conditions provides the feasible solution sets, and the algorithm based on dynamic programming is designed for phased optimization. Experimental results show that the proposed optimization model considering competence differences can solve the problem effectively.

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Ju, Chun Hua, and Yi Xie. "An Extended CPM for Resource-Constrained Project Scheduling." Advanced Materials Research 69-70 (May 2009): 695–99. http://dx.doi.org/10.4028/www.scientific.net/amr.69-70.695.

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In order to apply traditional CPM in resource-constrained project scheduling, the activity network is firstly formalized for resource-constrained project scheduling. Then Resource constraint in project is presented and an algorithm of the extended CPM is developed for resource-constrained project scheduling. Finally a case is conducted, which shows the accuracy and effectiveness of the extend CPM.

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ULUSOY, G., and L. ÖZDAMAR. "A constraint-based perspective in resource constrained project scheduling." International Journal of Production Research 32, no. 3 (1994): 693–705. http://dx.doi.org/10.1080/00207549408956961.

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Liu, Shu Shun, and Wei Tong Chen. "Construction Multi-Project Scheduling Model Considering Different Resource Allocation Behavior." Applied Mechanics and Materials 174-177 (May 2012): 2815–19. http://dx.doi.org/10.4028/www.scientific.net/amm.174-177.2815.

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According to previous researches, an investigation through small to mid-size construction contractors showed that 84% of construction contractors execute their projects in a multi-project environment. In a multi-project environment, scheduling problems with resource constraints are much more complicated than those in a single project. One of the most important factors that influence multi-project scheduling problems is resource allocation policy, depending on the types of resources, which can be defined by the way of resource acquisition and sharing behavior. This paper discusses resource allocation mechanism for construction multi-project scheduling issues, and then presents an optimization-based model to resolve resource allocation problems. This research developed a CP-based (Constraint Programming) model, which is capable of handling different optimization objectives such as minimizing total cost, overall project duration, subject to resource assignment combinations for each activity. Based on research results, the influence of different types of resource quantity on multi-project duration is discussed. Moreover, resource competitive behavior among all projects is recognized. It concludes that the effective increment of critical resources can reduce overall project duration. The major goal of this research is to find the relation among duration-cost-resource in a multi-project environment, and provide systematic information for construction parties when making resource allocation decisions.

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Kannimuthu, Marimuthu, Benny Raphael, Palaneeswaran Ekambaram, and Ananthanarayanan Kuppuswamy. "Comparing optimization modeling approaches for the multi-mode resource-constrained multi-project scheduling problem." Engineering, Construction and Architectural Management 27, no. 4 (2019): 893–916. http://dx.doi.org/10.1108/ecam-03-2019-0156.

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Purpose Construction firms keep minimal resources to maintain productive working capital. Hence, resources are constrained and have to be shared among multiple projects in an organization. Optimal allocation of resources is a key challenge in such situations. Several approaches and heuristics have been proposed for this task. The purpose of this paper is to compare two approaches for multi-mode resource-constrained project scheduling in a multi-project environment. These are the single-project approach (portfolio optimization) and the multi-project approach (each project is optimized individually, and then heuristic rules are used to satisfy the portfolio constraint). Design/methodology/approach A direct search algorithm called Probabilistic Global Search Lausanne is used for schedule optimization. Multiple solutions are generated that achieve different trade-offs among the three criteria, namely, time, cost and quality. Good compromise solutions among these are identified using a multi-criteria decision making method, Relaxed Restricted Pareto Version 4. The solutions obtained using the single-project and multi-project approaches are compared in order to evaluate their advantages and disadvantages. Data from two sources are used for the evaluation: modified multi-mode resource-constrained project scheduling problem data sets from the project scheduling problem library (PSPLIB) and three real case study projects in India. Findings Computational results prove the superiority of the single-project approach over heuristic priority rules (multi-project approach). The single-project approach identifies better solutions compared to the multi-project approach. However, the multi-project approach involves fewer optimization variables and is faster in execution. Research limitations/implications It is feasible to adopt the single-project approach in practice; realistic resource constraints can be incorporated in a multi-objective optimization formulation; and good compromise solutions that achieve acceptable trade-offs among the conflicting objectives can be identified. Originality/value An integer programming model was developed in this research to optimize the multiple objectives in a multi-project environment considering explicit resource constraints and maximum daily costs constraints. This model was used to compare the performance of the two multi-project environment approaches. Unlike existing work in this area, the model used to predict the quality of activity execution modes is based on data collected from real construction projects.

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Wikarek, Jarosław, and Paweł Sitek. "A Constraint-Based Declarative Programming Framework for Scheduling and Resource Allocation Problems." Vietnam Journal of Computer Science 06, no. 01 (2019): 69–90. http://dx.doi.org/10.1142/s2196888819500027.

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Scheduling and resource allocation problems are widespread in many areas of today’s technology and management. Their different forms and structures appear in production, logistics, software engineering, computer networks, project and human resources management, services, etc. The literature (problem classification, scheduling and resource allocation models, solutions) is vast and exhaustive. In practice, however, classical scheduling problems with fixed structures and standard constraints (precedence, disjoint, etc.) are rare. Practical scheduling problems include also logical and nonlinear constraints, and they use nonstandard criteria of schedule evaluations. Indeed, in many cases, decision makers are interested in the feasibility and/or optimality of a given schedule for specified conditions formulated as general and/or specific questions. Thus, there is a need to develop a programming framework that will facilitate the modeling and solving of a variety of diverse scheduling problems. The framework should be able to (a) model any types of constraints, (b) ask questions/criteria relating to the schedule execution mode and (c) be highly effective in finding solutions (schedule development). This paper proposes such a constraint-based declarative programming framework for modeling and solving scheduling problems which satisfies the assumptions above. It was built with the Constraint Logic Programming (CLP) environment and supported with Mathematical Programming (MP). The functionality and effectiveness of this framework are presented with the use of an illustrative example for the resource-constrained scheduling problem with additional resources.

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Qu, Chang Zheng, Hong Qiang Gu, Hui Song, and Guang Yu Liu. "Maintenance Project Scheduling Model Considered Flexible Resource with Capability Difference." Advanced Materials Research 791-793 (September 2013): 1566–69. http://dx.doi.org/10.4028/www.scientific.net/amr.791-793.1566.

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Maintenance task scheduling during mission break is described as flexible resource constraint project scheduling problem, and flexible resource constraint maintenance task scheduling model is established. Since capability level of flexible resource is different, the thesis establishes maintenance task scheduling model considering capability difference. To resolve the model, a particle swarm optimization (PSO) algorithm based on activity list is presented. At last, a case study is present.

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Xie, Linlin, Yajiao Chen, and Ruidong Chang. "Scheduling Optimization of Prefabricated Construction Projects by Genetic Algorithm." Applied Sciences 11, no. 12 (2021): 5531. http://dx.doi.org/10.3390/app11125531.

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Prefabricated buildings are the direction of the future development of the construction industry and have received widespread attention. The effective execution of prefabricated construction project scheduling should consider resource constraints and the supply arrangement of prefabricated components. However, the traditional construction resource-constrained project scheduling implementation method cannot simultaneously consider the characteristics of the linkage between component production and on-site assembly construction. It cannot also fully adapt to the scheduling implementation method of the prefabricated construction projects. It is difficult to work out a reasonable project schedule and resource allocation table. In order to determine the relevant schedule parameters that can reflect the actual construction situation of the prefabricated building and meet the scheduling requirements of the prefabricated project, this study proposes a prefabricated construction project scheduling model that considers project resource constraints and prefabricated component supply constraints. Additionally, it improves the design of traditional genetic algorithms (GAs). Research results of the experimental calculation and engineering application show that the proposed project scheduling optimization model and GA are effective and practical, which can help project managers in effectively formulating prefabricated construction project scheduling plans, reasonably allocating resources, reducing completion time, and improving project performance.

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Dang Quoc, Huu, Loc Nguyen The, Cuong Nguyen Doan, and Toan Phan Thanh. "A NEW ALGORITHM FOR MULTI-SKILL RESOURCE CONSTRAINED PROJECT SCHEDULING PROBLEM BASED ON CUCKOO SEARCH STRATEGY." Journal of Science Natural Science 65, no. 6 (2020): 98–109. http://dx.doi.org/10.18173/2354-1059.2020-0034.

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The purpose of this paper is to consider the project scheduling problem under such limited constraint, called Multi-Skill Resource-Constrained Project Scheduling Problem or MS-RCPSP. The algorithm proposed in this paper is to find the optimal schedule, determine the start time for each task so that the execution time (also called makespan) taken is minimal. At the same time, our scheduling algorithm ensures that the given priority relationships and constraints are not violated. Our scheduling algorithm is built based on the Cuckoo Search strategy. In order to evaluate the proposed algorithm, experiments were conducted by using the iMOPSE dataset. The experimental results proved that the proposed algorithm found better solutions than the previous algorithm.

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Liess, Olivier, and Philippe Michelon. "A constraint programming approach for the resource-constrained project scheduling problem." Annals of Operations Research 157, no. 1 (2007): 25–36. http://dx.doi.org/10.1007/s10479-007-0188-y.

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Isah, Muritala Adebayo, and Byung-Soo Kim. "Integrating Schedule Risk Analysis with Multi-Skilled Resource Scheduling to Improve Resource-Constrained Project Scheduling Problems." Applied Sciences 11, no. 2 (2021): 650. http://dx.doi.org/10.3390/app11020650.

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Construction projects are planned in a complex and dynamic environment characterized by high risks and uncertainties amidst resource constraints. Assessing construction schedule risk facilitates informed decision-making, especially in a resource-constrained situation, and allows proactive actions to be taken so that project objectives are not jeopardized. This study presents a stochastic multiskilled resource scheduling (SMSRS) model for resource-constrained project scheduling problems (RCSPSP) considering the impact of risk and uncertainty on activity durations. The SMSRS model was developed by integrating a schedule risk analysis (SRA) model (developed in MS Excel) with an existing multiskilled resource scheduling (MSRS) algorithm for the development of a feasible and realistic schedule. The computational experiment carried out on three case projects using the proposed SMSRS model revealed an average percentage deviation of 10.50%, indicating the inherent risk and uncertainty in activity durations of the project schedule. The core contribution of the proposed SMSRS model is that it: (1) presents project practitioners with a simple tool for assessing the risks and uncertainty associated with resource-constrained project schedules so that necessary response actions can be taken to ensure project success; (2) provides the small-scale construction businesses with an affordable tool for evaluating schedule risk and developing a feasible and realistic project schedule.

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Isah, Muritala Adebayo, and Byung-Soo Kim. "Integrating Schedule Risk Analysis with Multi-Skilled Resource Scheduling to Improve Resource-Constrained Project Scheduling Problems." Applied Sciences 11, no. 2 (2021): 650. http://dx.doi.org/10.3390/app11020650.

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Construction projects are planned in a complex and dynamic environment characterized by high risks and uncertainties amidst resource constraints. Assessing construction schedule risk facilitates informed decision-making, especially in a resource-constrained situation, and allows proactive actions to be taken so that project objectives are not jeopardized. This study presents a stochastic multiskilled resource scheduling (SMSRS) model for resource-constrained project scheduling problems (RCSPSP) considering the impact of risk and uncertainty on activity durations. The SMSRS model was developed by integrating a schedule risk analysis (SRA) model (developed in MS Excel) with an existing multiskilled resource scheduling (MSRS) algorithm for the development of a feasible and realistic schedule. The computational experiment carried out on three case projects using the proposed SMSRS model revealed an average percentage deviation of 10.50%, indicating the inherent risk and uncertainty in activity durations of the project schedule. The core contribution of the proposed SMSRS model is that it: (1) presents project practitioners with a simple tool for assessing the risks and uncertainty associated with resource-constrained project schedules so that necessary response actions can be taken to ensure project success; (2) provides the small-scale construction businesses with an affordable tool for evaluating schedule risk and developing a feasible and realistic project schedule.

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Mahalleh, Milad Keshavarz Kord, Behzad Ashjari, Fereshteh Yousefi, and Morteza Saberi. "A Robust Solution to Resource-Constraint Project Scheduling Problem." INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS 17, no. 3 (2017): 221–27. http://dx.doi.org/10.5391/ijfis.2017.17.3.221.

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Et.al, Rozi Nor Haizan Nor. "Project Scheduling Management in the Software Industry." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 3 (2021): 2136–45. http://dx.doi.org/10.17762/turcomat.v12i3.1156.

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Project scheduling is the next step once project planning is completed. This requires knowledge and the depth of the activities, the dependencies between activities and, duration of the activities. Creating and designing a realistic project schedule is the biggest challenges a project manager faces. There are some common problems that can be impact towards project delay or performance: Assigning Resource or Resource Constraint, Managing the Unknown or Managing Change and Estimating Task Duration. These 3 factors and causes are contributing to project scheduling problem. The impact of resource constraint causes towards be impact towards project delay or performance. To achieve this goal, the survey has been conducted. Finally, the results of the surveys are presented in order to see which commons problems are the most happening and really effected project scheduling.

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Zhao, Xinhui, Xuezhi Lü, Qiyi Mei, and Weidong Feng. "Project Scheduling Problem Constrained by Flexible Resource with Capability Difference." International Journal of Engineering and Technology 7, no. 6 (2015): 502–7. http://dx.doi.org/10.7763/ijet.2015.v7.845.

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Biruk, S., and P. Jaśkowski. "Scheduling Linear Construction Projects with Constraints on Resource Availability." Archives of Civil Engineering 63, no. 1 (2017): 3–15. http://dx.doi.org/10.1515/ace-2017-0001.

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AbstractProduction rates for various activities and overall construction project duration are significantly influenced by crew formation. Crews are composed of available renewable resources. Construction companies tend to reduce the number of permanent employees, which reduces fixed costs, but at the same time limits production capacity. Therefore, construction project planning must be carried out by means of scheduling methods which allow for resource constrains. Authors create a mathematical model for optimized scheduling of linear construction projects with consideration of resources and work continuity constraints. Proposed approach enables user to select optimal crew formation under limited resource supply. This minimizes project duration and improves renewable resource utilization in construction linear projects. This paper presents mixed integer linear programming to model this problem and uses a case study to illustrate it.

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Ali, Mazhar, Saif Ullah, and Mirza Jahanzaib. "A RESOURCE OPTIMISATION BASED HEURISTIC FOR RESOURCE CONSTRAINED PROJECT SCHEDULING PROBLEM." NED University Journal of Research XVI, no. 4 (2019): 115–24. http://dx.doi.org/10.35453/nedjr-ascn-2018-0092.

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Resource constrained project scheduling problem has significant application in industries. Although several heuristic solutions have been developed in the literature to address this problem, most of these have lesser focus on scheduling of shared and scarce resources. The presented study proposes a resource optimisation based heuristic (ROBH) to optimise the utilisation of shared resources so as to minimise the penalty cost of projects. The proposed ROBH identifies shared resources within the project activities and shifts the activities from the bottleneck resource to the residual resources. The performance of the proposed ROBH was tested using the standard benchmark instances of project scheduling problems available in the existing literature. The results were compared with those obtained from the heuristics available in the project scheduling problem library. This comparison indicated that the results provided by ROBH are significant as compared to the results obtained from the heuristics available in the literature.

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Udosen, U. J. "Application of #Chain Equations to Resource Scheduling." Advanced Materials Research 824 (September 2013): 544–52. http://dx.doi.org/10.4028/www.scientific.net/amr.824.544.

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Chain (pronounced number chain) equations were applied in the resource scheduling of two projects. The first project involved the scheduling of one type of manpower with unlimited resource availability while the second involved categorized manpower with resource constraints. The Earliest Start (ES), Latest Start (LS) and Leveling methods were applied to schedule the first project and were characterized by plotting network diagrams to schedule the project. When the #Chain approach was employed to schedule the same project, plotting of network diagrams was obviated but yielded similar manpower profiles and project duration of 12 weeks as the other methods. The ES, LS and Leveling methods did not lend themselves to scheduling of the project with categorized manpower having constraints and were not applied for scheduling the second project. However, the #Chain equations were applied, with ease, to schedule the second project to generate manpower profiles for each type of manpower. Due to the constraints applied, the project duration was extended from 12 weeks to 14 weeks. Hence the #Chain approach proffers a simple and preferred methodology for scheduling categorized resources with their attendant constraints.

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Suresh, M., Pankaj Dutta, and Karuna Jain. "Resource Constrained Multi-Project Scheduling Problem with Resource Transfer Times." Asia-Pacific Journal of Operational Research 32, no. 06 (2015): 1550048. http://dx.doi.org/10.1142/s0217595915500487.

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Scheduling multi-project is a complex decision making process. It involves the effective and timely allocation of resources to different projects. In the case of multi-project, resources are often transferred between the projects. It consumes both time and cost, when projects are situated in different geographic locations. As a result, the net present value (NPV) of multi-projects is significantly impacted by the resource transfer time. In this paper, a new genetic algorithm (GA) approach to the multi-project scheduling problem with resource transfer times is presented, where the NPV of all projects is maximized subject to renewable resource constraints. The paper also presents a heuristic approach using two phase priority rules for the same problem. We conduct a comprehensive analysis of 60 two-phase priority rules. The proposed GA approach is compared to the heuristic approach using the well-known priority rules. An extensive computational experiment is reported.

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Paek, In-Soub, Tae-Ho Ahn, and Yoon-Jae Cho. "Resource Constrained Project Scheduling Problem." Academic Society of Global Business Administration 17, no. 1 (2020): 207–32. http://dx.doi.org/10.38115/asgba.2020.17.1.207.

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Tosselli, Laura, Verónica Bogado, and Ernesto Martínez. "Multi-agent Learning by Trial and Error for Resource Leveling during Multi-Project (Re)scheduling." Journal of Computer Science and Technology 18, no. 02 (2018): e14. http://dx.doi.org/10.24215/16666038.18.e14.

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In a multi-project context within enterprise networks, reaching feasible solutions to the (re)scheduling problem represents a major challenge, mainly when scarce resources are shared among projects. The multi-project (re)scheduling must achieve the most efficient possible resource usage without increasing the prescribed project constraints, considering the Resource Leveling Problem (RLP), whose objective is to level the consumption of resources shared in order to minimize their idle times and to avoid overallocation conflicts. In this work, a multi-agent solution that allows solving the Resource Constrained Multi-project Scheduling Problem (RCMPSP) and the Resource Investment Problem is extended to incorporate indicators on agents’ payoff functions to address the Resource Leveling Problem in a decentralized and autonomous way, through decoupled rules based on Trial-and-Error approach. The proposed agent-based simulation model is tested through a set of project instances that vary in their structure, parameters, number of resources shared, etc. Results obtained are assessed through different scheduling goals, such as project total duration, project total cost and leveling resource usage. Our results are far better compared to the ones obtained with alternative approaches. This proposal shows that the interacting agents that implement decoupled learning rules find a solution which can be understood as a Nash equilibrium.

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Kastor, A., and K. Sirakoulis. "The effectiveness of resource levelling tools for Resource Constraint Project Scheduling Problem." International Journal of Project Management 27, no. 5 (2009): 493–500. http://dx.doi.org/10.1016/j.ijproman.2008.08.006.

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Semenov, Vitaly, Anton Anichkin, Sergey Morozov, Oleg Tarlapan, and Vladislav Zolotov. "Effective Project Scheduling Under Workspace Congestion and Workflow Disturbance Factors." Australasian Journal of Construction Economics and Building - Conference Series 2, no. 1 (2014): 35. http://dx.doi.org/10.5130/ajceb-cs.v2i1.3768.

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Effective project management implies the use of advanced planning and scheduling methods that allow to determine feasible sequences of activities and to complete a project on time and on budget. Traditional scheduling tools like fundamental Critical Path Method (CPM) and various methods for Resource Constrained Project Scheduling Problem (RCPSP) and Time Constrained Project Scheduling Problem (TCPSP) have many shortcomings for construction projects where spatial factor plays a critically important role. Previous attempts to interpret space as a specific resource were successful for particular problems of line-of-balance scheduling, space scheduling, dynamic layout planning, horizontal and vertical logic scheduling, workspace congestion mitigating, scheduling multiple projects with movable resources, spatial scheduling of repeated and grouped activities and motion planning. However, none of these methods considers the spatio-temporal requirements in a holistic framework of generic RCPSP problem and provides feasible results accounting for workspace and workflow factors. In this paper we start with the classical RCPSP statement and then present mathematically strong formalisation of the extended generalised problem, taking into account workspace congestion and workflow disturbance constraints specified in practically meaningful and computationally constructive ways. For the generalised RCPSP problem an effective scheduling method is proposed. The method tends to minimise the project makespan while satisfying timing constraints and precedence relations, not exceeding resource utilisation limits, avoiding workspace congestions and keeping workflows continuous. The method reuses so-called serial scheduling scheme and provides for additional computational routines and heuristic priority rules to generate feasible schedules satisfying all the imposed requirements. Advantages of the method and prospects for its application to industrial needs are outlined in the paper too.

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Kosztyán, Zsolt T., and István Szalkai. "Multimode resource-constrained project scheduling in flexible projects." Journal of Global Optimization 76, no. 1 (2019): 211–41. http://dx.doi.org/10.1007/s10898-019-00832-8.

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Abstract Flexible agile and extreme project management methods have become increasingly popular among practitioners, particularly in the IT and R&D sectors. In contrast to the theoretically and algorithmically well-established and developed trade-off and multimode methods applied in traditional project management methods, flexible project scheduling methods, which are applied in agile, hybrid, and especially extreme project management, lack a principled foundation and algorithmic handling. The aim of this paper is to fill this gap. We propose a matrix-based method that provides scores for alternative project plans that host flexible task dependencies and undecided, supplementary task completion while also handling the new but unplanned tasks. In addition, traditional multimode resource-constrained project scheduling problems are also covered. The proposed method can bridge the flexible and traditional approaches.

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Huang, Hsiang-Hsi, Ching-Hsu Huang, and Pei Wen. "Solving Multi-Resource Constrained Project Scheduling Problem using Ant Colony Optimization." Journal of Engineering, Project, and Production Management 5, no. 1 (2015): 2–12. http://dx.doi.org/10.32738/jeppm.201501.0002.

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Özdamar, Linet, and Gündüz Ulusoy. "A local constraint based analysis approach to project scheduling under general resource constraints." European Journal of Operational Research 79, no. 2 (1994): 287–98. http://dx.doi.org/10.1016/0377-2217(94)90359-x.

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Li, Yan, Zhi Run Xiao, Wen Qing Dou, and Ying Yang. "A Constraint-Based Approach for Skilled Workforce Scheduling Problem." Applied Mechanics and Materials 536-537 (April 2014): 1669–73. http://dx.doi.org/10.4028/www.scientific.net/amm.536-537.1669.

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The Skilled Workforce Project Scheduling Problem (SWPSP) is a complex problem of task scheduling and resource assignment that comes up in the daily management of many company Service Centers. In this paper we present a constraint programming (CP) approach for the SWPSP. We extend the project scheduling literature by developing a project scheduling model that accounts for differing skills among workers. The computational results for the SWPSP show that the constraint programming approach increases the performance of the model solving processes. The results for the SWPSP is effective in solving the proposed problem.

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Li, Yan, Zhi Run Xiao, Wen Qing Dou, and Ying Yang. "A Constraint-Based Approach for Skilled Workforce Scheduling Problem." Applied Mechanics and Materials 631-632 (September 2014): 1295–99. http://dx.doi.org/10.4028/www.scientific.net/amm.631-632.1295.

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The Skilled Workforce Project Scheduling Problem (SWPSP) is a complex problem of task scheduling and resource assignment that comes up in the daily management of many company Service Centers. In this paper we present a constraint programming (CP) approach for the SWPSP. We extend the project scheduling literature by developing a project scheduling model that accounts for differing skills among workers. The computational results for the SWPSP show that the constraint programming approach increases the performance of the model solving processes. The results for the SWPSP is effective in solving the proposed problem.

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Li, Yan, and Zhi Run Xiao. "A Constraint-Based Approach for Multi-Skilled Project Scheduling Problem." Applied Mechanics and Materials 681 (October 2014): 265–69. http://dx.doi.org/10.4028/www.scientific.net/amm.681.265.

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The problem of multi-skilled project scheduling (MSPSP) is a complex problem of task scheduling and resource assignment that comes up in the daily management of many software company. In this paper we present a constraint programming (CP) approach for the MSPSP. We extend the project scheduling literature by developing a project scheduling model that accounts for differing skills among workers. The computational results for the MSPSP show that the constraint programming approach increases the performance of the model solving processes. The results for the MSPSP is effective in solving the proposed problem.

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Özkan, Ömer, and Ümit Gülçiçek. "A NEURAL NETWORK FOR RESOURCE CONSTRAINED PROJECT SCHEDULING PROGRAMMING." Journal of Civil Engineering and Management 21, no. 2 (2015): 193–200. http://dx.doi.org/10.3846/13923730.2013.802723.

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The resource constrained project-scheduling problem (RCPSP) aims to minimize the duration of a project. RCPSP is prevalently used in programming the projects with high number of activities and resources such as construction projects. In this study, 240 projects such as residential, office, school, etc. are designed and programmed under limited resources. The resource amounts of these projects are determined using three priority rules, these are Latest Finish Time, Minimum Slack Time and Maximum Remaining Path Length which have the highest performance according to the literature, in the amounts of 2, 4, 6 and 8. The project times are estimated using artificial neural network (ANN). A correlation coefficient of 0.70 was obtained from the ANN estimation model.

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RUHLUSARAÇ, Murat, and Filiz ÇALIŞKAN. "A MATHEMATICAL MODEL FOR DYNAMIC PROJECT SCHEDULING PROBLEM AND REACTIVE SCHEDULING IMPLEMENTATION." Business & Management Studies: An International Journal 8, no. 4 (2020): 83–97. http://dx.doi.org/10.15295/bmij.v8i4.1708.

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In today's real-life implementations, projects are executed under uncertainty in a dynamic environment. In addition to resource constraints, the baseline schedule is affected due to the unpredictability of the dynamic environment. Uncertainty-based dynamic events experienced during project execution may change the baseline schedule partially or substantially and require projects' rescheduling. In this study, a mixed-integer linear programming model is proposed for the dynamic resource-constrained project scheduling problem. Three dynamic situation scenarios are solved with the proposed model, including machine breakdown, worker sickness, and electricity power cut. Finally, generated reactive schedules are completed later than the baseline schedule.

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Tam, Paul Wing Ming, and Pujitha Bandara Gamagedera Dissanayake. "Construction project scheduling by ranked positional weight method." Canadian Journal of Civil Engineering 25, no. 3 (1998): 424–36. http://dx.doi.org/10.1139/l97-100.

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Construction projects are commonly scheduled by the critical path method or its similar methods, with the assumption that resources are unlimited. The ranked positional weight method, which may be used for project scheduling and resource allocation for both constrained and unconstrained resource scheduling, is found to be relatively easy in application. In construction, the availability of resources is sometimes limited and this leads to an extension of project duration. The critical path method and similar approaches cannot provide an answer in this scenario. A bridge construction project is used to illustrate how the method can be applied.Key words: scheduling, resource allocation, ranked positional weight method.

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Kim, Jin-Lee. "Improved genetic algorithm for resource-constrained scheduling of large projects." Canadian Journal of Civil Engineering 36, no. 6 (2009): 1016–27. http://dx.doi.org/10.1139/l09-049.

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The generalized model of the resource-constrained project scheduling problem (RCPSP) is valuable because it can be incorporated into the advanced computational methods of commercial project management software for practical applications. A construction schedule generated by most commercial project management programs does not guarantee its optimality when the resources are limited. This paper presents an improved elitist genetic algorithm (GA) for resource-constrained scheduling of large projects. The proposed algorithm allocates multiple renewable resources to activities of a single large-sized project to achieve the objective of minimizing the project duration. A permutation-based decoding procedure is developed using the improved parallel schedule generation scheme. A new parameter, named transformation power, is created in the transformation method of the improved algorithm to ensure that the individual selection process performs correctly. Extensive computational results using a standard set of large-sized multiple resource-constrained project scheduling problems are presented to demonstrate the performance and accuracy of the algorithm.

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Kong, Feng, and Dong Dou. "Resource-Constrained Project Scheduling Problem under Multiple Time Constraints." Journal of Construction Engineering and Management 147, no. 2 (2021): 04020170. http://dx.doi.org/10.1061/(asce)co.1943-7862.0001990.

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Ammar, Mohammad A., and Youssef A. Mohieldin. "Resource constrained project scheduling using simulation." Construction Management and Economics 20, no. 4 (2002): 323–30. http://dx.doi.org/10.1080/01446190210131098.

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Yu, Xiao Guang, De Chen Zhan, and Lan Shun Nie. "A Novel Heuristic Algorithm for Spatial Resource Constrained Project Scheduling Problem." Applied Mechanics and Materials 58-60 (June 2011): 1448–53. http://dx.doi.org/10.4028/www.scientific.net/amm.58-60.1448.

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Spatial resources such as slipway and erection platform are key and bottleneck resources for large equipment manufacturing enterprises, and restrict output and efficiency of enterprises. Spatial resource has several distinct features, such asspatiality,divisibility,adjacency,exclusivityandgroupcharacteristic. These features introduce great complexities into spatial Resource Constrained Project Scheduling Problem (sRCPSP), which lead sRCPSP very hard to model and solve. So a mathematical model for sRCPSP considered all features and other renewable resource constrains comprehensively has been established. Then an Activity Type Priority based Serial Scheduling heuristic method and a Resource-Time Block based Spatial Resource Allocation Method have been proposed to solve the model. Results of numerical experiments proved that those two algorithms are correct and effective.

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Tam, Paul Wing Ming, and Ekambaram Palaneeswaran. "The use of enhanced positional weight method for constrained resources project scheduling." Canadian Journal of Civil Engineering 26, no. 2 (1999): 242–47. http://dx.doi.org/10.1139/l98-052.

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Scheduling of construction projects is normally performed with the critical path method (CPM). The popular CPM/PERT network techniques are based on the assumption that sufficient resources will be available when needed to complete all project activities on schedule. This unrealistic assumption can lead to ineffective resource usage and project delays. For scheduling of the project activities with resource constraints, other algorithms have to be used. This technical note first outlines the suitability of ranked positional weight method (RPWM), a heuristic resource scheduling method, to construction project scheduling. It then focuses on a new heuristic technique, the enhanced positional weight method (EPWM), which is an improved version of the RPWM. Some interesting comparisons between the results given by Primavera, Microsoft Project, RPWM, and EPWM are also presented.Key words: ranked positional weight method, enhanced positional weight method, and critical path method.

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Chakrabortty, Ripon K., Ruhul A. Sarker, and Daryl L. Essam. "Single mode resource constrained project scheduling with unreliable resources." Operational Research 20, no. 3 (2018): 1369–403. http://dx.doi.org/10.1007/s12351-018-0380-7.

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Zheng, Zheng, Lin Shumin, Guo Ze, and Zhu Yueni. "Resource-constraint Multi-project Scheduling with Priorities and Uncertain Activity Durations." International Journal of Computational Intelligence Systems 6, no. 3 (2013): 530–47. http://dx.doi.org/10.1080/18756891.2013.789152.

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Khattab, M., and F. Choobineh. "A new heuristic for project scheduling with a single resource constraint." Computers & Industrial Engineering 19, no. 1-4 (1990): 514–18. http://dx.doi.org/10.1016/0360-8352(90)90171-h.

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Khattab, M., and F. Choobineh. "A new heuristic for project scheduling with a single resource constraint." Computers & Industrial Engineering 20, no. 3 (1991): 381–87. http://dx.doi.org/10.1016/0360-8352(91)90010-4.

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Kaveh, A., M. Khanzadi, and M. Alipour. "Fuzzy Resource Constraint Project Scheduling Problem Using CBO and CSS Algorithms." International Journal of Civil Engineering 14, no. 5 (2016): 325–37. http://dx.doi.org/10.1007/s40999-016-0031-4.

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Kellenbrink, Carolin, and Stefan Helber. "Scheduling resource-constrained projects with a flexible project structure." European Journal of Operational Research 246, no. 2 (2015): 379–91. http://dx.doi.org/10.1016/j.ejor.2015.05.003.

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Zhang, Zhao, Bing Guo, Gui Xiang Chen, and Jiu Le Song. "The Review of Project Management Based on the Theory of Constraints and Critical Chain." Applied Mechanics and Materials 174-177 (May 2012): 3424–30. http://dx.doi.org/10.4028/www.scientific.net/amm.174-177.3424.

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Abstract. The relationship between precedence and successor activities is the only factor that determined the project scheduling in the traditional project scheduling management. The critical chain-an elegant solution, on the other hand, takes resource limitations into account and is composed of sections that are dependent on successor relationships and other sections that are dependent on resource constraint. By integrating the existing research findings, it is the objective of this paper to highlight the merits and pitfalls of the CCPM scheduling method, such as the principle for project delays, the critical chain identification; the time buffer setting and project scheduling with limited capacity of a resource. Furthermore, it also presidents the difficulties when implementing the critical chain approach and conclude with a description of our ongoing research direction.

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Demassey, Sophie, Christian Artigues, and Philippe Michelon. "Constraint-Propagation-Based Cutting Planes: An Application to the Resource-Constrained Project Scheduling Problem." INFORMS Journal on Computing 17, no. 1 (2005): 52–65. http://dx.doi.org/10.1287/ijoc.1030.0043.

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Liu, Shu-Shun, Muhammad Faizal Ardhiansyah Arifin, Wei Tong Chen, and Ying-Hua Huang. "Emergency Repair Scheduling Model for Road Network Integrating Rescheduling Feature." Applied Sciences 11, no. 4 (2021): 1447. http://dx.doi.org/10.3390/app11041447.

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When a natural disaster occurs, road maintenance departments always face the challenge of how to assign repair resources properly to recover damaged road segments as soon as possible. From the literature review, most studies treat such problems as a vehicle routing problem (VRP). In those studies, repair resources are always dispatched as complete crews, and cannot be divided into smaller scales. Furthermore, each disaster point is only allowed one group of resources to recover it, without considering the possibility of accelerating the production rate subjected to specific objectives. Such limitation restricts required resources in an inflexible manner. Therefore, this study defines all repair works as an emergency repair project and adopts the framework of the Resource-Constrained Project Scheduling Problem (RCPSP), which can resolve such complicated resource assignment issue. A novel emergency repair scheduling model for the road network is proposed based on Constraint Programming (CP) as the searching algorithm to facilitate model formulation. According to the RCPSP concepts, disaster points are set as repair activities and resource travel routes between disaster points are set as transit activities. All the repair activities are linked by transit activities and the required resources are assigned accordingly. In order to consider the second-wave hazard events of where new disaster points may occur, and new resources may be added into emergency repair projects, a rescheduling feature is integrated into the proposed model. Through two case studies, research findings show that this model can be easily modulated to adapt to different situations satisfying practical disaster management goals and solving emergency repair scheduling problems for road networks efficiently.

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Klimek, M., and P. Łebkowski. "Resource allocation for robust project scheduling." Bulletin of the Polish Academy of Sciences: Technical Sciences 59, no. 1 (2011): 51–55. http://dx.doi.org/10.2478/v10175-011-0008-z.

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Resource allocation for robust project schedulingThe paper presents a formal description of the resource allocation problem for resource-constrained project scheduling. A schedule can be executed by various resource flow networks which may differ in terms of resistance to disruptions occurring during project execution. The authors define such criteria of evaluating a resource flow network which can be more useful than robustness metrics used so far in the research. The authors discuss the importance of robust scheduling for execution projects and propose metrics for resource allocation robustness which take into consideration the stability of the final schedule. Those metrics make it possible to carry out a more precise analysis concerning the properties of the resource flow network in terms of its robustness to disruptions in comparison with a well known flexibility indicator,flex.

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Wang, Xixi, Farouk Yalaoui, and Frédéric Dugardin. "Non-dominated Sorting Genetic Algorithms for a Multi-objective Resource Constraint Project Scheduling Problem." Journal of Intelligent Systems 28, no. 5 (2017): 791–806. http://dx.doi.org/10.1515/jisys-2017-0241.

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Abstract The resource constraint project scheduling problem (RCPSP) has attracted growing attention since the last decades. Precedence constraints are considered as well as resources with limited capacities. During the project, the same resource can be required by several in-process jobs and it is compulsory to ensure that the consumptions do not exceed the limited capacities. In this paper, several criteria are involved, namely makespan, total job tardiness, and workload balancing level. Our problem is firstly solved by the non-dominated sorting genetic algorithm-II (NSGAII) as well as the recently proposed NSGAIII. Giving emphasis to the selection procedure, we apply both the traditional Pareto dominance and the less documented Lorenz dominance into the niching mechanism of NSGAIII. Hence, we adopt and modify L-NSGAII to our problem and propose L-NSGAIII by integrating the notion of Lorenz dominance. Our methods are tested by 1350 randomly generated instances, considering problems with 30–150 jobs and different configurations of resources and due dates. Hypervolume and C-metric are considered to evaluate the results. The Lorenz dominance leads the population more toward the ideal point. As experiments show, it allows improving the original NSGA approach.

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Kim, Kyunghwan. "Generalized Resource-Constrained Critical Path Method to Improve Sustainability in Construction Project Scheduling." Sustainability 12, no. 21 (2020): 8918. http://dx.doi.org/10.3390/su12218918.

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Delays by limited supply of resources are common in many construction projects and may cause serious monetary disputes between project participants. Since the dispute resolution may require unnecessary additional time and cost, preventing delays in advance is an important goal in sustainable construction project management. To prevent delays, a feasible plan must be implemented, which reflects limited resources and provides reliable activity information. For this purpose, this study proposes a generalized resource-constrained critical path method (eRCPM). It consists of three steps to identify resource-dependent activity relationships (resource links) based on the result of resource-constrained scheduling (RCS) under multiple resource constraints. Compared to the existing resource-constrained critical path methods, the eRCPM has the advantage of identifying resource links irrespective of the applied RCS technique because it is based on the result rather than the RCS process. Further, this study presents a Microsoft (MS) Excel-based half-automated prototype system that is linked using file export and import functions to both P6 and MS Project software packages. The detailed process of the eRCPM algorithm and the operation process of the prototype system are described using an example schedule. Through a case study, it was demonstrated that eRCPM appropriately identifies the necessary resource links and provides reliable total floats.

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Journal articles on the topic 'Resource constraint project scheduling'

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