A Multi-objective Resource-constrained Project Scheduling Problem Using Genetic Algorithm
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Resource-Constrained Project Scheduling Problem (RCPSP) has been modeled as a single or multi-objectives, using minimization of project make-span, lateness, total weighted start time, total project cost and maximization of project net present value. In this paper, a multi-objective RCPSP incorporated resource idleness into the list of RCPSP objectives. Here, the RCPSP is modeled as a Mixed Integer Non-Linear Programme to depict the various objective factors namely cost, time and resource idleness. Genetic algorithm (GA) meta-heuristic solution technique is used to promote solution diversity and determine the Pareto optimal for the multi-objective problem. The performance of the proposed RCPSP model was evaluated using a standard test problem that consist of 5 activities, 3 reusable resource types and a network diagram; a comprehensive computational experiment was performed and the results were analyzed with precedence relations considering the objectives as single objectives, bi-objectives and in combined form as multi-objectives simultaneously. The integration of resources idleness into the multi-objective policy gives more realistic result.
Multi-Objective, Resource-Constrained, Project Scheduling Problem, Genetic Algorithm, Precedence Relations
OGUNWOLU, L., Sosimi, A., & Salahudeen, T. (2018). A Multi-Objective Resource-Constrained Project Scheduling Problem Using Genetic Algorithm. FUTA Journal of Engineering and Engineering Technology, 12(1), 90-101.