Solving resource-constrained project scheduling problems: Conceptual validation of FLP formulation and efficient permutation-based ABC computation

• Published in: Computers & operations research Vol. 40; no. 8; pp. 2037 - 2050
• Main Authors: Jia, Qiong, Seo, Yoonho
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01.08.2013; Elsevier; Pergamon Press Inc
• Subjects: Algorithms; Applied sciences; Artificial bee colony optimization; Colonies; Computation; Computer simulation; Exact sciences and technology; Facilities management; Facility layout problem; Integer programming; Inventory control, production control. Distribution; Mathematical models; Operational research and scientific management; Operational research. Management science; Operators; Optimization algorithms; Permutation representation scheme; Project management; Resource allocation; Resource-constrained project scheduling problem; Scheduling; Scheduling, sequencing; Searching; Studies; Swarm intelligence; Resource-constrained project scheduling problem; Facility layout problem; Permutation representation scheme; Artificial bee colony optimization; Operator equation; Permutation; Project management; Scheduling; Layout problem; Makespan; scheduling problem; Overlap; Resource-constrained project; Modeling; Optimization; NP hard problem; Swarm intelligence; Plant layout; Resource management
• ISSN: 0305-0548; 1873-765X; 0305-0548
• DOI: 10.1016/j.cor.2013.02.012

In this paper, we propose two alternative approaches, applying the facility layout problem (FLP) concept and integrating the permutation-based artificial bee colony (PABC) algorithm, to effectively tackle the resource-constrained project scheduling problem (RCPSP). In the FLP formulation, the constraints are expressed to design the activities in the space constructed by resource and temporal restrictions, without violating the precedence relationships and overlaps between the activities. For dodging the difficulty of the FLP-based model to treat large-sized instances of NP-hard RCPSP, the permutation representation scheme of the PABC algorithm is in turn introduced utilizing the artificial bee colony (ABC) process to search the best solution for RCPSP. In the procedure, a crossover operator and an insert operator following the update equation of the ABC algorithm are devised to augment the effectiveness of computation, whereas a shift operator subject to the resource utilization ratio value is suggested to diversify the solutions. The makespan is then obtained and improved with the assistance of a serial scheduling scheme and a double justification skill. Subsequently, the computational experiments conducted substantiate the conceptual validity of the proposed facility layout formulation for RCPSP and the comprehensive simulation shows the effectiveness of the PABC algorithm for RCPSP.