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

Author

Qiao, Dongping, Wang, Yajing, Pei, Jie, Bai, Wentong, and Wen, Xiaoyu

Subjects
*ANT algorithms, *SCHEDULING, *ANTS, *ENERGY consumption, *PROBLEM solving, *SETUP time
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. [ABSTRACT FROM AUTHOR]

Published
2022
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