Abstracto

A multi-objective intelligent algorithm for cells formation

Jun Gong, Xiuyang Chen, Sen Zhang

Cells formation based on production requirements with a planning horizon and multiple objectives was addressed. This paper develops a nonlinear multi-objective mathematical method for dynamic cell formation with three objectives, including the total cost in the process of cell formation, the maximum deviation of load with available capacities of machines, and the total number of inter-cell moves. This paper propose an adaptive niche technique, penalty technique, double roulette wheel method, and reserving elite strategy, reserving elite-based random weight multi-objective genetic algorithm for the complicated combination optimization model. The model and algorithm are analyzed by a numerical example. The numerical results demonstrate that the proposed genetic algorithm is effective and efficient