New hybrid differential evolution for parallel machines batch scheduling
WANG Wan-liang，FAN Li-xia，XU Xin-li，ZHANG Jing

（College of Computer Science and Technology，Zhejiang University of Technology，Hangzhou 310023，China）
Abstract：Considering the characteristics of more products，small batches in practical production，a parallel machines batch scheduling model with process constraint was established. In order to solve the problem of splitting，a new batch splitting method based on demand and new chromosome representation was put forward. A new parallel encoding was brought forward to solve both the batch splitting problem and batch scheduling problem. To the problem of low searching speed and premature convergence appeared in standard differential evolution，a new hybrid differential evolution（DE），based on dynamic random search and Chaos optimization，was proposed to enhance local search ability of standard DE. Performance of the proposed algorithm on classic benchmark function and shop scheduling demonstrate that，the proposed algorithm can effectively improve searching speed，balancing the abilities of global search and local search.

Key words：differential evolution（DE）；dynamic random search；local search（LS）；parallel machines scheduling；batch process