A multi-objective vibration damping optimization algorithm for solving a cellular manufacturing system with manpower and tool allocation

Abstract

In this paper, a novel bi-objective mathematical model is proposed to design a four-dimensional (i.e., part, machine, operator, and tool) Cellular Manufacturing System (CMS) in a dynamic environment. The main objectives of this model are to: (1) Minimize total costs including tools processing cost, costs of transporting cells between various cells, machine setup cost, and operators' educational costs and (2) Maximize the skill level of operators. The developed model is strictly NP-hard and exact algorithms cannot find globally optimal solutions in a reasonably computational amount of time. Thus, a Multi- Objective Vibration Damping Optimization (MOVDO) algorithm with a new solution structure that satisfies all the constraints and generates feasible solutions is proposed to find near-optimal solutions in a reasonably computational amount of time. Since there is no benchmark available in the literature, three other meta-heuristic algorithms (i.e., Non-dominated Sorting Genetic Algorithm-II (NSGA-II), Multi-Objective Particle Swarm Optimization (MOPSO), and Multi-Objective Invasive Weeds Optimization (MOIWO)) with a similar solution structure are developed to validate the performance of the proposed MOVDO algorithm for solving various instances of the developed model. The result of comparing their performances based on statistical tests and different measuring metrics reveals that the proposed MOVDO algorithm remarkably outperforms other meta-heuristics used in this paper.