Solving resource-constrained project scheduling problem with evolutionary programming

• Published in: The Journal of the Operational Research Society Vol. 64; no. 9; pp. 1327 - 1335
• Main Authors: Sebt, M H, Alipouri, Y
• Format: Journal Article
• Language: English
• Published: London Taylor & Francis 01.09.2013; Palgrave Macmillan; Palgrave Macmillan UK; Taylor & Francis Ltd
• Subjects: Algorithms; Business and Management; Cost functions; Evolution; evolutionary programming; General Paper; General Papers; Genetic algorithms; Heuristics; Management; Mathematical functions; Mathematical minima; Methods; Minimization of cost; Operations research; Operations Research/Decision Theory; Optimization; Population; Project management; random key representation; resource-constrained project scheduling; Schedules; Scheduling; Social evolution; Studies; random key representation; resource-constrained project scheduling; project management; evolutionary programming
• ISSN: 0160-5682; 1476-9360
• DOI: 10.1057/jors.2012.69

This paper presents an evolutionary programming (EP)-based approach to solving the resource-constrained project scheduling problem (RCPSP), a well-known NP-hard problem in scheduling, with minimization of project duration as the objective subject to precedence and resource constraints. The individual representation of EP for the problem is based on random keys. The serial generation scheme is used in the decoding scheme to generate the project plan. Experimental analyses are presented to investigate the performance of the proposed EP-based methodology, including comparison of the four variants of EP, namely, CEP, FEP, MCEP and IMCEP, with each other and GA to find the best variant of EP for the RCPSP, and comparison of this best variant of EP (MCEP) with other approaches using the J30 standard instances set in PSPLIB. The computational results validate the effectiveness of the proposed algorithm.