Abstract
The multi-mode resource-constrained project scheduling problem (MRCPSP) has been identified to be an NP-hard problem. MRCPSP includes solving two sub-problems: mode assignment and activity priority determination. Hence, two particle swarm optimizations (PSOs) are applied to each sub-problem. A constriction PSO is proposed for the activity priority determination and a discrete PSO is for the mode assignment. Least total resource usage (LTRU) and minimum slack (MSLK) heuristics ensure better initial solutions. Hence, to generate a collection of diverse initial solutions and thereby enhance the PSO efficiency, a best heuristic rate (HR) is suggested. To verify the performance, all instances of the MRCPSP benchmarks in PSPLIB were evaluated. The experimental results reveal that the proposed algorithm has high performance and is efficient for solving the MRCPSP problems. Therefore, a real-world man-day project scheduling problem (MDPSP) was evaluated and the results demonstrate that MDPSP can be solved successfully.
Highlights
The results demonstrate that the proposed algorithm outperforms other algorithms for the multimode resource-constrained project scheduling problem (MRCPSP) problems
The well-known resource-constrained project scheduling problem (RCPSP) is a combinatorial optimization problem where activities are scheduled such that the makespan is minimized, while satisfying given precedence constraints between the activities and resources
The solution quality is measured by evaluating the ratio of optimal solutions (OPT) found which is calculated using (12); “besti” represents the best solution found for instance i
Summary
The well-known resource-constrained project scheduling problem (RCPSP) is a combinatorial optimization problem where activities are scheduled such that the makespan is minimized, while satisfying given precedence constraints between the activities and resources. The scheduling target of MRCPSP is to find an adequate mode assignment for each activity and determine a satisfactory activity priority while satisfying the constraints, minimizing the makespan. Scheduling problems such as job-shop, flow-shop, and vehicle routing have been studied intensively, and are confirmed to be NP-complete in their general forms. Different man-day combinations are considered as a different operation modes This manday project scheduling problem (MDPSP) can be regarded as a MRCPSP problem.
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