Evolutionary computation on multicriteria production process planning problem

The production process planning (PPP) problem is abundant among manufacturing systems. In general the problem can be approached by network analysis or dynamic programming. It is difficult for traditional optimization techniques to cope with the multicriteria production process planning (mPPP) problem. In this paper, a new evolutionary computation (EC) approach is developed to deal with the PPP problems with both single or multiple objective criteria. The proposed EC approach adopts a new simple state permutation encoding and combines with the neighborhood search technique in mutation operation to improve the evolutionary process in finding the optimal solution of the PPP problems. The numerical analysis shows that the proposed EC is both effective and efficient for the PPP problems