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resource-constrained project scheduling problem under Multiple Time Constraints

JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT 2021年第2期147卷

作者： Kong, Feng Dou, Dong North China Elect Power Univ Dept Econ Management Baoding 071003 Hebei Peoples R China

This paper introduces a new practical scheduling problem called the resource-constrained project scheduling problem under multiple time constraints, which involves a duration constraint of activity, temporal constraint, and resource calendar constraint. The duration constraint of the activity exists widely in real-life projects, and it is first proposed as a resource-constrained project scheduling problem in this paper. We prove the defects of the traditional temporal constraint and improve it. The new problem combines three types of time constraints for the first time, which makes it closer to the actual scheduling problem. We developed a constraint programming optimization model for the new problem and used the IBM ILOG CPLEX-CP version 12.9.0 optimizer to solve it. Computational experiments are carried out to show that the CP optimizer is fast and provides a near-optimum solution to the new problem for projects with hundreds of activities within minutes compared to other metaheuristic methods. The results reported in this paper can be used as a benchmark for other researchers to compare and improve. The new problem contributes to developing a practical decision support system for resolving real-life constraints in projects.

关键词： project scheduling resource-constrained project scheduling problem Multiple time constraints CPLEX Constraint programming

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A novel heuristic algorithm with activity back-shift response model for resource-constrained project scheduling problem

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SOFT COMPUTING 2019年第17期23卷 7805-7819页

作者： Sheng, Buyun Wang, Hui Xiao, Zheng Zhang, Chenglei Zhao, Feiyu Yin, Xiyan Wuhan Univ Technol Sch Mech & Elect Engn Wuhan 430070 Hubei Peoples R China

The resource-constrained project scheduling problem is one of the most intractable problems in the field of operation research and management science. It is important for both academic research and engineering applications to develop effective solution algorithms for scheduling problems. In this paper, the activity back-shift response model is introduced for scheduling problems, based on which a resource-constrained scheduling model is built, and a two-phase decomposition algorithm is proposed to address the project resource-constraint and timing optimization. The first stage is resource optimization, where the conflicted activities are resolved by a genetic algorithm. In this case, if parallel activities are scrambling resources during resource optimization, the activity priority, determined by comparing the activity back-shift response time, is applied to dissolve the resource conflict. The second stage is timing optimization. After obtaining the progress plan with optimized resource constraints, activities are adjusted to move forward as much as possible. The validity of the proposed algorithm is verified by a real project case. The computational results reveal that the proposed model and algorithm obtain appropriate results and have the potential to be applied to other similar problems.

关键词： resource-constrained project scheduling problem Activity back-shift response model resource conflict resolution Makespan

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Solving resource-constrained project scheduling problem via Genetic Algorithm

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JOURNAL OF COMPUTING IN CIVIL ENGINEERING 2020年第2期34卷

作者： Liu, Jia Liu, Yisheng Shi, Ying Li, Jian China Construct Sci & Technol Changchun Co Ltd Dept Engn Management Changchun 130033 Peoples R China Beijing Jiaotong Univ Sch Econ & Management Beijing 100044 Peoples R China Beijing Jiaotong Univ Dept Engn Management Beijing 100044 Peoples R China China Univ Min & Technol Beijing Sch Management Beijing 100044 Peoples R China Natl Res Ctr Rehabil Tech Aids Minist Civil Affairs Beijing Key Lab Rehabil Tech Aids Old Age Disabil Key Lab Intelligent Control & Rehabil Technol Beijing 100176 Peoples R China

The resource-constrained project scheduling problem (RCPSP) is an important and challenging problem in the field of construction management. This paper presents a genetic algorithm (GA) for the RCPSP. The proposed algorithm introduces several changes in the genetic algorithm paradigm, such as a new selection operator to select parents to recombine;a modified two-point crossover operator with a specific crossover order;and a linearly decreasing probability-based mutation operator. The proposed algorithm was tested using standard benchmark problems of size J30, J60, and J120 from project scheduling problem Library (PSPLIB) and compared with 19 state-of-the-art metaheuristics in the literature. The computational results validate that the proposed algorithm is a competitive algorithm for solving the RCPSP.

关键词： Construction management Genetic algorithm resource-constrained project scheduling problem

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An improved particle swarm optimization for the resource-constrained project scheduling problem

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2013年第9-12期67卷 2627-2638页

作者： Jia, Qiong Seo, Yoonho Korea Univ Dept Informat Management Engn Seoul 136713 South Korea

In this paper, an improved particle swarm optimization (PSO) algorithm is proposed for the resource-constrained project scheduling problem (RCPSP) which is widely applied in advanced manufacturing, production planning, and project management. The algorithm treats the solutions of RCPSP as particle swarms and employs a double justification skill and a move operator for the particles, in association with rank-priority-based representation, greedy random search, and serial scheduling scheme, to execute the intelligent updating process of the swarms to search for better solutions. The integration combines and overhauls the characteristics of both PSO and RCPSP, resulting in enhanced performance. The computational experiments are subsequently conducted to set the adequate parameters and compare the proposed algorithm with other approaches. The results suggest that the proposed PSO algorithm augments the performance by 9.26, 16.17, and 10.45 % for the J30, J60, and J120 instances against the best lower bound-based PSO currently available, respectively. Moreover, the proposed algorithms demonstrate obvious advantage over other proposals in exploring solutions for large-scale RCPSP problems such as the J60 and J120 instances.

关键词： resource-constrained project scheduling problem Particle swarm optimization Rank-priority-based presentation Double justification Move operator

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A branch and bound algorithm for the resource-constrained project scheduling problem

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 1998年第2期107卷 272-288页

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

A branch and bound algorithm is presented for the resource-constrained project scheduling problem (RCPSP). Given are n activities which have to be processed without preemptions. During the processing period of an activity constant amounts of renewable resources are needed where the available capacity of each resource type is limited. Furthermore, finish-start precedence relations between the activities are given. The objective is to determine a schedule with minimal makespan. The branching scheme starts from a graph representing a set of conjunctions (the classical finish-start precedence constraints) and disjunctions (induced by the resource constraints). Then it either introduces disjunctive constraints between pairs of activities or places these activities in parallel. Concepts of immediate selection are developed in connection with this branching scheme. Immediate Selection allows to add conjunctions as well as further disjunctions and parallelity relations. Computational results based on the test data of Kolisch ct al. (Kolisch, R., Sprecher, A., Drexl. A., 1995. Management Science 41, 1693-1703.) and Kolisch and Sprecher (Kolisch, R., Sprecher, A., 1997. PSPLIB - A project scheduling problem library, EJOR 96, pp. 205-216.) are reported. (C) 1998 Elsevier Science B.V. All rights reserved.

关键词： branch and bound method immediate selection resource-constrained project scheduling problem disjunctive graph model

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A column-generation-based algorithm for a resource-constrained project scheduling problem with a fractional shared resource

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ENGINEERING OPTIMIZATION 2020年第5期52卷 798-816页

作者： Wang, Qiang Liu, Changchun Zheng, Li Tsinghua Univ Dept Ind Engn Beijing Peoples R China

This article considers a resource-constrained project scheduling problem with a single shared resource. In this model, multiple processors are required to complete jobs with a certain amount of shared resource. The supply of the resource is limited and must be shared between processors. A column-generation-based algorithm with some enhancement techniques, including stabilization, a mechanism to update the solution pool, and an approximate solution technique, is proposed. Finally, extensive computational experiments are conducted to evaluate the performance of the proposed method by comparing it with Lagrangian relaxation, CPLEX and a self-adapting genetic algorithm. The results prove the proposed method has an advantage in terms of the objective and CPU time. Numerical experiments are also conducted to verify the effectiveness of the proposed enhancements.

关键词： resource-constrained project scheduling problem total weighted tardiness column generation limit resource

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Genetic algorithm for the resource-constrained project scheduling problem

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AUTOMATION AND REMOTE CONTROL 2017年第6期78卷 1101-1114页

作者： Goncharov, E. N. Leonov, V. V. Novosibirsk State Univ Novosibirsk Russia Russian Acad Sci Siberian Branch Sobolev Inst Math Novosibirsk Russia

We consider the resource-constrained project scheduling problem with respect to the makespan minimization criterion. The problem accounts for technological constraints of activities precedence together with resource constraints. We propose a genetic algorithm with two versions of crossovers based on the idea of most rational use of constrained resources. The crossovers uses a heuristic that takes into account the degree of criticality for the resources, which is derived from the solution of a relaxed problem with a constraint on accumulative resources. A numerical experiment with examples from the PCPLIB library has shown that the proposed algorithm has competitive quality. For some examples from the j120 test series the best known solutions were improved and for j60 (50 000 and 500 000 iterations) and for j120 (500 000 iterations) we have obtain the best average deviations of the solutions from the critical path value.

关键词： resource-constrained project scheduling problem renewable resources genetic algorithms PCPLIB

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New meta-heuristics for the resource-constrained project scheduling problem

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FLEXIBLE SERVICES AND MANUFACTURING JOURNAL 2013年第1-2期25卷 48-73页

作者： Lim, Andrew Ma, Hong Rodrigues, Brian Tan, Sun Teck Xiao, Fei City Univ Hong Kong Dept Management Sci Kowloon Tong Hong Kong Peoples R China Zhejiang Univ Dept Management Sci & Engn Sch Management Hangzhou 310003 Zhejiang Peoples R China Singapore Management Univ Lee Kong Chian Sch Business Singapore Singapore Natl Univ Singapore Dept Comp Sci Singapore 117548 Singapore Google Inc Mountain View CA USA

In this paper, we study the resource-constrained project scheduling problem and introduce an annealing-like search heuristic which simulates the cooling process of a gas into a highly-ordered crystal. To achieve this, we develop diversification procedures that simulate the motion of high energy molecules as well as a local refinement procedure that simulates the motion of low energy molecules. We further improve the heuristic by incorporating a genetic algorithm framework. The meta-heuristic algorithms are applied to Kolisch's PSPLIB J30, J60 and J120 RCPSP instances. Experimental results show that they are effective and are among the best performing algorithms for the RCPSP.

关键词： resource-constrained project scheduling problem Meta-heuristics Genetic algorithms

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Particle swarm optimization with justification and designed mechanisms for resource-constrained project scheduling problem

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EXPERT SYSTEMS WITH APPLICATIONS 2011年第6期38卷 7102-7111页

作者： Chen, Ruey-Maw Natl Chin Yi Univ Technol Dept Comp Sci & Informat Engn Taichung 411 Taiwan

The studied resource-constrained project scheduling problem (RCPSP) is a classical well-known problem which involves resource, precedence, and temporal constraints and has been applied to many applications. However, the RCPSP is confirmed to be an NP-hard combinatorial problem. Restated, it is hard to be solved in a reasonable time. Therefore, there are many metaheuristics-based schemes for finding near optima of RCPSP were proposed. The particle swarm optimization (PSO) is one of the metaheuristics, and has been verified being an efficient nature-inspired algorithm for many optimization problems. For enhancing the PSO efficiency in solving RCPSP, an effective scheme is suggested. The justification technique is combined with PSO as the proposed justification particle swarm optimization (JPSO), which includes other designed mechanisms. The justification technique adjusts the start time of each activity of the yielded schedule to further shorten the makespan. Moreover, schedules are generated by both forward scheduling particle swarm and backward scheduling particle swarm in this work. Additionally, a mapping scheme and a modified communication mechanism among particles with a designed gbest ratio (GR) are also proposed to further improve the efficiency of the proposed JPSO. Simulation results demonstrate that the proposed JPSO provides an effective and efficient approach for solving RCPSP. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： scheduling Particle swarm optimization Justification resource-constrained project scheduling problem

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Improved discrete cuckoo search for the resource-constrained project scheduling problem

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APPLIED SOFT COMPUTING 2018年 69卷 493-503页

作者： Bibiks, Kirils Hu, Yim-Fun Li, Jian-Ping Pillai, Prashant Smith, Aleister Univ Bradford Fac Engn & Informat Bradford BD7 1DP W Yorkshire England

An Improved Discrete Cuckoo Search (IDCS) is proposed in this paper to solve resource-constrained project scheduling problems (RCPSPs). The original Cuckoo Search (CS) was inspired by the breeding behaviour of some cuckoo species and was designed specifically for application in continuous optimisation problems, in which the algorithm had been demonstrated to be effective. The proposed IDCS aims to improve the original CS for solving discrete scheduling problems by reinterpreting its key elements: solution representation scheme, Levy flight and solution improvement operators. An event list solution representation scheme has been used to present projects and a novel event movement and an event recombination operator has been developed to ensure better quality of received results and improve the efficiency of the algorithm. Numerical results have demonstrated that the proposed IDCS can achieve a competitive level of performance compared to other state-of-the-art metaheuristics in solving a set of benchmark instances from a well-known PSPLIB library, especially in solving complex benchmark instances. Crown Copyright (C) 2018 Published by Elsevier B.V. All rights reserved.

关键词： scheduling resource-constrained project scheduling problem Cuckoo search Metaheuristics Combinatorial optimisation

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