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research-article

A cooperative co-evolutionary algorithm for large-scale process planning with energy consideration

[+] Author and Article Information
Fei Tao

School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, P. R. China
ftao@buaa.edu.cn

Luning Bi

School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, P. R. China
biluning@buaa.edu.cn

Ying Zuo

School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, P. R. China
zuoying226@126.com

A Y C Nee

Department of Mechanical Engineering, National University of Singapore 117576, Singapore
mpeneeyc@nus.edu.sg

1Corresponding author.

ASME doi:10.1115/1.4035960 History: Received March 03, 2016; Revised December 23, 2016

Abstract

Process planning can be an effective way to improve the energy efficiency of production processes. Aimed at reducing both energy consumption and processing time, a comprehensive approach which considers feature sequencing, process selection and physical resources allocation simultaneously, is established in this paper. As the number of decision variables increase, process planning becomes a large-scale problem, and it is difficult to be addressed by simply employing a regular meta-heuristic algorithm. A cooperative co-evolutionary algorithm, which hybridizes the artificial bee colony algorithm (ABCA) and Tabu search (TS), is therefore proposed. In addition, in the proposed algorithm, a novel representation method is designed to generate feasible process plans under complex precedence. Compared with some widely-used algorithms, the proposed algorithm is proven to have a good performance for handling large-scale process planning in terms of maximizing energy efficiency and production times.

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