Mechanical Engineering

Wenwen Lin This email address is being protected from spambots. You need JavaScript enabled to view it.1, Lei Wang1 , Rengkai Zhou1 , Yuejun Zhang1 and Chaoyong Zhang2

1Faculty of Mechanical Engineering & Mechanics, Ningbo University, Ningbo 315211, P.R. China
2State Key Laboratory of Digital Manufacturing Equipment & Technology, Huazhong University of Science & Technology, Wuhan 430074, P.R. China

 

Received: January 9, 2018
Accepted: June 13, 2018
Publication Date: December 1, 2018

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

ABSTRACT

In job shop scheduling problems, the previously used nonpreemptive schedules are semiactive, 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.


Keywords: Job Shop, Energy-efficient Scheduling, Nonpreemptive Schedule, Genetic Algorithm, Statistical Test


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