Process plan generation in reconfigurable manufacturing systems using adapted NSGA-II and AMOSA

Abstract

Reconfigurable manufacturing system (RMS) is a manufacturing paradigm that cost-effectively responses to market changes. This paper addresses the multi-objective process plan generation problem in RMS. More specifically, two meta-heuristics, namely Non-dominated Sorting Genetic Algorithm (NSGA-II) and Archived Multi-Objective Simulated Annealing (AMOSA), are adapted to generate near-optimal process plans. With the help of a numerical example, the performances of the two metaheuristics are demonstrated and compared.