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A Genetic Algorithm with Neighborhood Search for the resource-constrained project scheduling problem

NAVAL RESEARCH LOGISTICS 2011年第2期58卷 73-82页

作者： Proon, Sepehr Jin, Mingzhou Mississippi State Univ Mississippi State MS 39762 USA Univ Pittsburgh Pittsburgh PA USA

The resource-constrained project scheduling problem (RCPSP) consists of a set of non-preemptive activities that follow precedence relationship and consume resources. Under the limited amount of the resources, the objective of RCPSP is to find a schedule of the activities to minimize the project makespan. This article presents a new genetic algorithm (GA) by incorporating a local search strategy in GA operators. The local search strategy improves the efficiency of searching the solution space while keeping the randomness of the GA approach. Extensive numerical experiments show that the proposed GA with neighborhood search works well regarding solution quality and computational time compared with existing algorithms in the RCPSP literature, especially for the instances with a large number of activities. (C) 2011 Wiley Periodicals, Inc. Naval Research Logistics 58: 73-82, 2011

关键词： resource-constrained project scheduling problem genetic algorithm neighborhood search

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LSSPER: Solving the resource-constrained project scheduling problem with large neighbourhood search

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ANNALS OF OPERATIONS RESEARCH 2004年第1-4期131卷 237-257页

作者： Palpant, M Artigues, C Michelon, P Lab Informat Avignon F-84911 Avignon 9 France

This paper presents the Local Search with Subproblem Exact Resolution (LSSPER) method based on large neighbourhood search for solving the resource-constrained project scheduling problem (RCPSP). At each step of the method, a subpart of the current solution is fixed while the other part defines a subproblem solved externally by a heuristic or an exact solution approach (using either constraint programming techniques or mathematical programming techniques). Hence, the method can be seen as a hybrid scheme. The key point of the method deals with the choice of the subproblem to be optimized. In this paper, we investigate the application of the method to the RCPSP. Several strategies for generating the subproblem are proposed. In order to evaluate these strategies, and, also, to compare the whole method with current state-of-the-art heuristics, extensive numerical experiments have been performed. The proposed method appears to be very efficient.

关键词： resource-constrained project scheduling problem large neighbourhood search

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A hybrid evolutionary algorithm for the resource-constrained project scheduling problem

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ARTIFICIAL LIFE AND ROBOTICS 2012年第2期17卷 312-316页

作者： Thammano, Arit Phu-ang, Ajchara King Mongkuts Inst Technol Ladkrabang Fac Informat Technol Computat Intelligence Lab Bangkok 10520 Thailand

The resource-constrained project scheduling problem (RCPSP) is an NP-hard optimization problem. RCPSP is one of the most important and challenging problems in the project management field. In the past few years, many researches have been proposed for solving the RCPSP. The objective of this problem is to schedule the activities under limited resources so that the project makespan is minimized. This paper proposes a new algorithm for solving RCPSP that combines the concepts of negative selection mechanism of the biologic immune system, simulated annealing algorithm (SA), tabu search algorithm (TS) and genetic algorithm (GA) together. The performance of the proposed algorithm is evaluated and compared to current state-of-the-art metaheuristic algorithms. In this study, the benchmark data sets used in testing the performance of the proposed algorithm are obtained from the project scheduling problem library. The performance is measured in terms of the average percentage deviation from the critical path lower bound. The experimental results show that the proposed algorithm outperforms the state-of-the-art metaheuristic algorithms on all standard benchmark data sets.

关键词： resource-constrained project scheduling problem Metaheuristic Evolutionary algorithm

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Extending the resource-constrained project scheduling problem for disruption management

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3rd IEEE International Conference on Intelligent Systems

作者： Kuster, Juergen Jannach, Dietmar Univ Klagenfurt Inst Appl Informat Univ Str 65-67 A-9020 Klagenfurt Austria

ISBN: (纸本)9781424401956

This paper describes how the resource-constrained project scheduling problem (RCPSP) can be used as a basis for comprehensive disruption management, concerned with both rescheduling as well as potential structural process modifications. It is illustrated, how the RCPSP can be extended by the possibility to represent alternative activities and how the respective constructs can be used to describe various forms of typical interventions. Moreover, an approach for schedule optimization and the resolution of the generalized problem is presented, based on the combination of well-established methodologies and specific evolutionary operators. In an illustrative example it is finally shown how the proposed framework can be applied for the development of real-time decision support systems in the domain of airport ground process management.

关键词： real-time decision support disruption management resource-constrained project scheduling problem evolutionary algorithm

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A Forward–Backward Relax-and-Solve Algorithm for the resource-constrained project scheduling problem

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SN Computer Science 2023年第2期4卷 104页

作者： Etminaniesfahani, Alireza Gu, Hanyu Naeni, Leila Moslemi Salehipour, Amir School of Mathematical and Physical Sciences University of Technology Sydney Broadway Sydney 2007 NSW Australia School of the Built Environment University of Technology Sydney Broadway Sydney 2007 NSW Australia The University of Sydney Business School Darlington 2006 NSW Australia

scheduling projects under limited resource availability, which is called the resource-constrained project scheduling problem (RCPSP), has a wide range of real-world applications, e.g., in mining, manufacturing and supply chain. The RCPSP is NP-hard, and over the last five decades researchers attempted to propose various solution techniques for this challenging problem. The relax-and-solve (R&S) algorithm is a recently proposed method for solving various scheduling problems, such as job-shop and single and parallel machine scheduling problems. This research contributes to the existing research on the R&S by presenting an easy-to-implement and effective R&S method for solving RCPSP. Our R&S employs CPLEX CP optimizer as an optimization solver to generate and optimize schedules within a heuristic framework. We further improve the algorithm’s performance by employing forward–backward passes. The results of testing the algorithms on 1560 standard instances from the well-known PSPLIB show our heuristic delivers competitive results and outperforms state-of-the-art methods for solving the RCPSP. © 2022, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Forward–backward improvement Matheuristic Relax-and-solve resource-constrained project scheduling problem

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Chaotic vibrating particles system for resource-constrained project scheduling problem

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SCIENTIA IRANICA 2020年第4期27卷 1826-1842页

作者： Kaveh, A. Vazirinia, Y. Iran Univ Sci & Technol Ctr Excellence Fundamental Studies Struct Engn POB 16846-13114 Tehran Iran

project scheduling in the resource-constrained situation is one of the key issues of project-oriented organizations. The aim of resource-constrained project scheduling problem (RCPSP) is to find a schedule with minimum makespan by considering precedence and resource constraints. RCPSP is a combinatorial optimization problem and belongs to the NP-hard class of problems. The exact methods search the entire search space and are unable to solve a large-sized project network problem. Thus, metaheuristics are used to solve this problem in a short computational time. Due to the probabilistic nature of metaheuristics, it is a challenging problem to make a balance between exploitation and exploration phases. The literature review shows that embedding of chaos improves both the convergence speed and the local optima avoidance of metaheuristics. This paper presents a Chaotic Vibrating Particles System (CVPS) optimization algorithm for solving the RCPSP. Vibrating Particles System (VPS) is a physics-inspired metaheuristic which mimics the free vibration of single-degree-of-freedom systems with viscous damping. The performance and applicability of the CVPS are compared with the standard VPS and five well-known algorithms on three benchmark instances of the RCPSPs. Experimental studies reveal that the proposed optimization method is a promising alternative to assist project managers in dealing with RCPSP. (C) 2020 Sharif University of Technology. All rights reserved.

关键词： resource-constrained project scheduling problem Metaheuristic algorithms Chaotic maps Chaotic vibrating particles system Chaos theory Global optimization

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Recent Trends in Solving the Deterministic resource constrained project scheduling problem 9th

Recent Trends in Solving the Deterministic Resource Constrai...

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9th Annual International Conference on Innovations in Information Technology (IIT)

作者： Karam, Ahmed Lazarova-Molnar, Sanja United Arab Emirates Univ Coll Informat Technol Al Ain U Arab Emirates

ISBN: (纸本)9781467362030

The classical resource-constrained project scheduling problem (RCPSP), a well-known NP-hard problem in scheduling, is one of the most extensively investigated problems in operations research. It has been attracting considerable attention from academia and industry for several decades. Recently, a number of new and promising meta-heuristic approaches for solving the RCPSP problem have emerged. In this paper, we provide a detailed review of the most recent approaches for solving the RCPSP that have been proposed in literature. In particular, we present a comparison, classification and analysis, based on a number of relevant metrics. Extensive numerical results based on well-known benchmark problem instance sets of size J30, J60 and J120 from project scheduling problem Library (PSPLIB), as well as comparisons among state-of-the-art hybrid meta-heuristic algorithms demonstrate the effectiveness of the proposed approaches for solving the RCPSP of various scales.

关键词： resource-constrained project scheduling problem operations researc review recent approaches comparison

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Lower bounds for resource-constrained project scheduling problems

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2003年第2期149卷 302-313页

作者： Brucker, P Knust, S Univ Osnabruck Fachbereich Math Informat D-49069 Osnabruck Germany

A destructive lower bound for the multi-mode resource-con strained project scheduling problem with minimal and maximal time-lags is presented. Given are n activities which may be processed in different modes without preemptions. During processing certain amounts of renewable and non-renewable resources are needed where the available capacity of each resource type is limited. Furthermore, minimal and maximal time-lags between the activities are given. The objective is to determine a schedule with minimal makespan. The lower bound calculations are based on two methods for proving infeasibility of a given threshold value T for the makespan. The first uses constraint propagation techniques, while the second is based on a linear programming formulation which is solved by a column generation procedure. Computational results are reported for several test instances of the multi-mode problem with and without time-lags and the single-mode version with time-lags. (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： scheduling resource-constrained project scheduling problem multi-mode lower bounds column generation constraint propagation

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A New MBS Representation for resource-constrained project scheduling problems

A New MBS Representation for Resource-Constrained Project Sc...

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IEEE Congress on Evolutionary Computation (CEC) held as part of IEEE World Congress on Computational Intelligence (IEEE WCCI)

作者： Hao, Xingxing Liu, Jing Xidian Univ Key Lab Intelligent Percept & Image Understanding Minist Educ Xian Peoples R China

ISBN: (纸本)9781509006229

In this paper, a new moving block sequence (MBS) representation for resource-constrained project scheduling problems (RCPSPs) is proposed, which is different from the classical activity list that has been widely used for RCPSPs. An activity in a project of RCPSPs has fixed duration and resource demands, thus, it can be modeled as a rectangle block whose height represents the resource demands and width the duration. Therefore, by modeling every activity in a project as a block, a project that consists of N activities can be represented as a permutation of N blocks that satisfy the precedence constraints. Then, for every activity in the project, four initial positions and corresponding move modes are designed, by using which activities can be moved from their initial positions to the appropriate locations that minimize the makespan of the project without violating the precedence and resource constraints. Based on this newly designed MBS representation, the multi-agent evolutionary algorithm (MAEA) is used for solving RCPSPs. The comparison with 16 existing state-of-the-art algorithms on benchmark J30 test set, which contains 480 instances in total, shows that the proposed algorithm is competitive in solving RCPSPs.

关键词： moving block sequence resource-constrained project scheduling problem evolutionary algorithm

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Lower bounds for resource-constrained project scheduling problems

Lower bounds for resource-constrained project scheduling pro...

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7th International Workshop on project Managment and scheduling

作者： Brucker, P Knust, S Univ Osnabruck Fachbereich Math Informat D-49069 Osnabruck Germany

关键词： scheduling resource-constrained project scheduling problem multi-mode lower bounds column generation constraint propagation

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