Multi-mode resource-constrained project scheduling problem with material ordering under bonus–penalty policies

This study emphasizes that project scheduling and material ordering (time and quantity of an order) must be considered simultaneously to minimize the total cost, as setting the material ordering decisions after the project scheduling phase leads to non-optimal solutions. Hence, this paper mathematic...

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Veröffentlicht in:TOP Jg. 25; H. 1; S. 49 - 79
Hauptverfasser: Zoraghi, Nima, Shahsavar, Aria, Abbasi, Babak, Van Peteghem, Vincent
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2017
Springer Nature B.V
Schlagworte:
Algorithms
Business and Management
Design of experiments
Economic Theory/Quantitative Economics/Mathematical Methods
Economics
Finance
Heuristic methods
Industrial and Production Engineering
Insurance
Management
Material requirements planning
Mathematical models
Nonrenewable resources
Operations Research/Decision Theory
Optimization
Original Paper
Policies
Production scheduling
Project management
Resource scheduling
Statistics for Business
Taguchi methods
90-02
Multi-mode resource-constrained
Genetic algorithm
90C11
Simulated annealing
90B35
Project scheduling
90B05
Particle swarm optimization
Material ordering
ISSN:1134-5764, 1863-8279
Online-Zugang:Volltext
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Zusammenfassung:This study emphasizes that project scheduling and material ordering (time and quantity of an order) must be considered simultaneously to minimize the total cost, as setting the material ordering decisions after the project scheduling phase leads to non-optimal solutions. Hence, this paper mathematically formulates the model for the multi-mode resource-constrained project scheduling with material ordering (MRCPSMO) problem. In order to be more realistic, bonus and penalty policies are included for the project. The objective function of the model consists of four elements: the material holding cost, the material ordering cost, the bonus paid by the client and the cost of delay in the project completion. Since MRCPSMO is NP-hard, the paper proposes three hybrid meta-heuristic algorithms called PSO-GA, GA-GA and SA-GA to obtain near-optimal solutions. In addition, the design of experiments and Taguchi method is used to tune the algorithms’ parameters. The proposed algorithms consist of two components: an outside search, in which the algorithm searches for the best schedule and mode assignment, and the inside search, which determines the time and quantity of orders of the nonrenewable resources. First, a comparison is made for each individual component with the exact or best solutions available in the literature. Then, a set of standard PROGEN test problems is solved by the proposed hybrid algorithms under fixed CPU time. The results reveal that the PSO-GA algorithm outperforms both GA-GA and SA-GA algorithms and provides good solutions in a reasonable time.
Bibliographie:ObjectType-Article-1
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ISSN:1134-5764
1863-8279
DOI:10.1007/s11750-016-0415-2