Title of article :
Integration of multi-mode resource-constrained project scheduling under bonus-penalty policies with material ordering under quantity discount scheme for minimizing project cost
Author/Authors :
Akhbari, M Department of Industrial Engineering - Electronic Branch - Islamic Azad University - Tehran, Iran
Pages :
20
From page :
427
To page :
446
Abstract :
In this paper, a mixed binary integer mathematical programming model is developed for integration of Multimode Resource-Constrainted Project Scheduling Problem (MRCPSP) under bonus-penalty policies and Quantity Discount Problem in Material Ordering (QDPMO) with the objective of minimizing the total project cost. By proving a theorem, an important property of the optimum solution of the problem is found, which reduces the search space signicantly compared to previous studies. Since the Resource- Constraint Project Scheduling Problem (RCPSP) belongs to the class of problems that are NP-hard, four hybrid meta-heuristic algorithms called COA-GA, GWO-GA, PSO-GA, and GA-GA are developed and tuned to solve the problem. Each of the proposed algorithms consists of outside and inside search components, which determine the best schedule and materials procurement plan, respectively. Finally, a set of standard PROGEN test problems is solved using the proposed hybrid algorithms under fixed CPU time. The results show that the COA-GA algorithm outperforms others.
Keywords :
Project scheduling , Multi-mode resourceconstrained , Quantity discount problem in material ordering , Grey wolf optimizer , Coyote optimization algorithm , Genetic algorithm , Particle swarm optimization
Journal title :
Scientia Iranica(Transactions E: Industrial Engineering)
Serial Year :
2022
Record number :
2706579
Link To Document :
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