Research on green single machine scheduling based on improved ant colony algorithm-Reference-Cited by-同舟云学术

Research on green single machine scheduling based on improved ant colony algorithm

Published:2021-12-20 Issue: Volume: Page:002029402110642
ISSN:0020-2940
Container-title:Measurement and Control
language:en
Short-container-title:Measurement and Control

Author:

Qiao Dongping¹²,Wang Yajing¹²^ORCID,Pei Jie¹²,Bai Wentong¹²,Wen Xiaoyu¹²

Affiliation:

1. College of Mechanical and Electrical Engineering, Zhengzhou University of Light Industry, Zhengzhou, China

2. Henan Key Laboratory of Intelligent Manufacturing of Mechanical Equipment, Zhengzhou University of Light Industry, Zhengzhou, China

Abstract

This paper studies the green single-machine scheduling problem that considers the delay cost and the energy consumption of manufacturing equipment and builds its integrated optimization model. The improved ant colony scheduling algorithm based on the Pareto solution set is used to solve this problem. By setting the heuristic information, state transition rules, and other core parameters reasonably, the performance of the algorithm is improved effectively. Finally, the model and the improved algorithm are verified by the simulation experiment of 10 benchmark cases.

Publisher

SAGE Publications

Subject

Applied Mathematics,Control and Optimization,Instrumentation

Link

http://journals.sagepub.com/doi/pdf/10.1177/00202940211064243

Reference52 articles.

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3. A discrete differential evolution algorithm for the single machine total weighted tardiness problem with sequence dependent setup times

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