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A multi-objective invasive weeds optimization algorithm for solving multi-skill multi-mode resource constrained project scheduling problem

Research paper by Hamidreza Maghsoudlou, Behrouz Afshar-Nadjafi, Seyed Taghi Akhavan Niaki

Indexed on: 18 Mar '16Published on: 03 Mar '16Published in: Computers & Chemical Engineering



Abstract

A new multi-skill multi-mode resource constrained project scheduling problem with three objectives is studied in this paper. The objectives are: (1) minimizing project's makespan, (2) minimizing total cost of allocating workers to skills, and (3) maximizing total quality of processing activities. A meta-heuristic algorithm called multi-objective invasive weeds optimization algorithm (MOIWO) with a new chromosome structure guaranteeing feasibility of solutions is developed to solve the proposed problem. Two other meta-heuristic algorithms called non-dominated sorting genetic algorithm (NSGA-II) and multi-objective particle swarm optimization algorithm (MOPSO) are used to validate the solutions obtained by the developed MOIWO. The parameters of the developed algorithms are calibrated using Taguchi method. The results of the experiments show that the MOIWO algorithm has better performance in terms of diversification metric, the MOPSO algorithm has better performance regarding mean ideal distance, while NSGA-II algorithm has better performance in terms of spread of non-dominance solution and spacing metrics.

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