Full-active Scheduling in Job Shop Problems Using an Improved Genetic Algorithm

Wenwen Lin ； Lei Wang ； Rengkai Zhou ； Yuejun Zhang ； Chaoyong Zhang

《淡江理工學刊》 21卷4期 (2018/12) Pp. 507-518

https://doi.org/10.6180/jase.201812_21(4).0002

摘要

In job shop scheduling problems, the previously used nonpreemptive schedules are semi-active, active, and non-delay schedules, and they are initially designed for traditional scheduling performances and do not take energy efficiency into consideration. To fill the gap, this article presents a novel class of nonpreemptive schedules by investigating the special properties of job shop scheduling problems. Then, an energy-efficient generation procedure of the novel nonpreemptive schedules and the standby policy are proposed. An improved genetic algorithm is introduced with three superior features, including the elitist selection, the improved generation alternation model, and the operator decision mechanism. The Friedman test and the Holm multiple comparison test are conducted on experimental results to determine the appropriate parameter for the proposed genetic algorithm. Finally, the computation results and two-sample t-tests show that both energy-efficient generation procedure and standby policy help to reduce energy consumption without worsening production efficiency.

關鍵字

Job Shop ； Energy-efficient Scheduling ； Nonpreemptive Schedule ； Genetic Algorithm ； Statistical Test