Utilizing the Modified Self-Adaptive Differential Evolution Algorithm in Dynamic Cellular Manufacturing System

Today, Cellular Manufacturing Systems (CMS) have been introduced as a mixture of work-shop manufacturing and line-production systems for keeping efficiency and flexibility synchronously. One of the difficult steps of designing CMS is the Cell Formation (CF) problem in which parts with similar processes are made in one cell. Solving a dynamic integer model of CF with three sub-objective functions is considered using evolutionary algorithms. Due to the fact that CF is a NP-hard problem, solving the model using classical optimization methods needs long computational time. In this paper, a nonlinear integer model of CF is presented and then solved by proposed Modified Self-adaptive Differential Evolution (MSDE) and Modified Genetic Algorithm (MGA) using a set of 25 test problems. The results are compared with the optimal solution, and the efficiency of MSDE algorithm is discussed. DOI: 10.4018/jamc.2012040101 2 International Journal of Applied Metaheuristic Computing, 3(2), 1-17, April-June 2012 Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. assume that problem data such as product mix and demand is constant for the entire planning horizon. Sometimes we face dynamic condition which input data in each period is different from the other periods but it is deterministic.