Optimization Algorithm Study for Multiple-Constrained and Multiple-Objective Job-Shop Tool Dynamic Distribution-Reference-Cited by-同舟云学术

Optimization Algorithm Study for Multiple-Constrained and Multiple-Objective Job-Shop Tool Dynamic Distribution

Published:2014-05 Issue: Volume:551 Page:612-616
ISSN:1662-7482
Container-title:Applied Mechanics and Materials
language:
Short-container-title:AMM

Author:

Wang Cui Yan¹,Du Wei Sheng¹,Wang Jun¹

Affiliation:

1. Shijiazhuang Tiedao University

Abstract

It’s an NP problem for distributing tools for job-shop tasks when the schedules were formulated, and it belongs to multiple-constrained and multiple-objective problem. Based on adaptive weight approach, the restriction and multiple objective problems were solved. The optimization dynamic distribution model for this problem was established. Then heuristic and self-adaptive genetic algorithm was presented. In order to express the dynamic of the distribution result, Two-dimensional coding technology was adopted, a new coding rule combining dispatching rule was designed. The results show that hybrid self-adaptive genetic algorithm based on adaptive weight approach forms well for multiple-constrained and multiple-objective job-shop tool dynamic distribution.

Publisher

Trans Tech Publications, Ltd.

Link

https://www.scientific.net/AMM.551.612.pdf

Reference6 articles.

1. Xuan Guangnan, Chen Runwei. Genetic Algorithms and Engineering Optimization[M]. Beijing: Tsinghua University Press, 2004, 76~100.

2. Ding Wuxue, Gong Guangrong, Wang Shuanghu, etc. The Dynamic Tools Planning Management for FMS[J]. Ordance Industry Automation . 2001, 20(4): 6~10.

3. He Jianyong. Optimization Methods[M]. Beijing: Tsinghua University Press, 2005. 417~461.

4. Yang Pingfan, Zhang Changshui. Artificial neural network simulation Evolutionary Computation[M]. Beijing: Tsinghua University Press, 2005. 550~606.

5. Wang Yuexuan, Liu Lianchen, MU Shengjing, etc . Constrained multi-objective optimization evolutionary algorithm [J]. Journal of Tsinghua University (Science and Technology) , 2005, 45(1): 103~106.

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Tool requirement and pre-scheduling optimization model of the tool flow system of a digital workshop;Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture;2017-03-20