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 manufactur- ing and line-production systems for keeping ef ciency and exibility synchronously. One of the dif cult 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 evolution- ary 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 Modi ed Self-adaptive Differential Evolution (MSDE) and Modi ed Genetic Algorithm (MGA) using a set of 25 test problems. The results are compared with the optimal solution, and the ef ciency of MSDE algorithm is discussed.