报告主题：Swarm and evolutionary algorithms for flexible job shop scheduling problems

报 告 人：高开周

报告时间：2017年12月25日（星期一）14:00

报告地点：计算机新大楼A401#

报告摘要：

      In this talk, the framework of swarm and evolutionary algorithms is introduced and the evolution strategies of GA and PSO is described. The flexible job shop scheduling problem (FJSP) is modelled. There is an example to explain the FJSP in detail. Two constraints, new job insertion and fuzz processing time, are considered in the FJSP. Swarm and evolutionary algorithms are employed an improved to solve the FJSP with constrains. Encoding and decoding strategies are developed for FJSP in population of swarm and evolutionary algorithms. Local search operators are developed to improve the performance of swarm and evolutionary algorithms. Experimental results and comparisons are shown to verify the performance of swarm and evolutionary algorithms. When the rescheduling operator is executed, the stability of existing scheduling are considered and the relationship between instability of reschedule and other objectives are discussed. Finally, personal achievement is summarized.

报告人简介：

         2016年博士毕业于新加坡南洋理工大学，现为南洋理工大学研究员。研究兴趣包括智能优化理论与算法、复杂系统建模与优化、生产调度、智能交通、港口优化调度等。主持国家自然科学基金1项、参与4项；作为实际完成人在研或完成新加坡科技发展局（A*Star）、新加坡经济发展局（EDB）项目和新加坡海事研究所项目3项。获山东省高等学校优秀科研成果奖一等奖1项，二等奖1项。发表学术论文50多篇，其中SCI论文19篇，他引 600多次，H指数13，I10指数15；在国际会议做专题报告及论文展示报告多次。担任30多个国际知名期刊及顶级国际会议编辑或审稿人。新加坡南洋理工大学 研究员 IEEE 会员。