近日，云师大李俊青教授课题组在《Expert Systems with Applications》杂志发表最新成果研究《A hybrid evolutionary immune algorithm for fuzzy flexible job shop schedul‐ ing problem with variable processing speeds 》。

据悉李俊青教授为云南师范大学高层次引进人才，现担任数学学院教授。

Abstract In this study, a fuzzy flexible job shop scheduling problem with variable processing speeds is considered. To address this problem, a multi-objective hybrid evolutionary immune algorithm (HEIA) is proposed, where the fuzzy maximum completion time (makespan) and fuzzy total energy consumption are optimized simultaneously. In the proposed HEIA, a two left-shift heuristic based active decoding method is proposed to optimize the fuzzy makespan. Then, two hybrid evolutionary strategies are used to separately enhance the exploration ability and exploitation ability, where a reference point-based angle selection strategy is incorporated to optimize the search mechanism. For the first evolutionary strategy, a Pareto similar information-based crossover operator is adopted to improve population diversity. For the second evolutionary strategy, a deep local search mechanism and four objective-driven neighborhood structures are developed. Finally, five types of instances are generated to verify the effectiveness of the proposed HEIA.

1-s2.0-S0957417423013933-main.pdf