Title: Job-shop schedule modelling and parents-crossover evolutionary optimisation for integrated production schedules

Authors: Jianxin Zhang; Jinxiang Chen; Haoyu Zhang

Addresses: Electric Power College, Inner Mongolia University of Technology Hohhot, Inner Mongolia, China ' State Key Laboratory of Hybrid Process Industry Automation Systems and Equipment, Technology, Automation Research and Design Institute of Metallurgical Industry, and Iron and Steel Research Institute Group, Beijing, 100081, China; Electric Power College, Inner Mongolia University of Technology Hohhot, Inner Mongolia, China ' Electric Power College, Inner Mongolia University of Technology Hohhot, Inner Mongolia, China

Abstract: An Improved Parent's Crossover Evolutionary Algorithm (IPCEA) is presented to deal with a class of job-shop scheduling optimisation problems in this paper. The considered integrated production process is firstly described as a job-shop model. Based on the model, the active schedules encoding and decoding approaches for production scheduling processes are proposed respectively. In order to avoid illegal chromosome and reserve the good characteristics of parent generation, an IPCEA is provided. Compared with the existing results, the proposed method can obtain better convergences and optimum solutions. The simulation results are given to show the effectiveness of our approaches.

Keywords: integrated production; SM-CC-HR; job-shop; IPPX-EA; ASD decode.

DOI: 10.1504/IJCAT.2018.095947

International Journal of Computer Applications in Technology, 2018 Vol.58 No.4, pp.288 - 295

Received: 05 Oct 2017
Accepted: 08 Nov 2017
Published online: 05 Nov 2018 *

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