Improved DE algorithm for multipurpose multistage batch scheduling problems

This paper introduces an improved differential evolution algorithm for solving short-term multipurpose multistage batch scheduling problems (MMBSP) with the objective of minimizing the maximum completion time of all batches. A novel individual encoding and decoding scheme is designed for representing a scheduling solution for MMBSP. To improve the performance of DE further, a local search mechanism is introduced to exploit more latitude of search space to anchor the global optimum. In addition, the proposed DE is combined with a position bound disturbance strategy to add population diversity. Using those strategies, the proposed DE algorithm can get good balance between exploitation and exploration. The experimental results on some random generated problem instances demonstrate the good performance of the proposed DE.