返回
Optimal process plan selection in networked based manufacturing using game-theoretic approach
DOI:10.1080/00207543.2012.682181.png)
摘要
En 中文
This paper proposes a scheme for generating optimal process plans for multi jobs in a networked based manufacturing system. Networked manufacturing offers several advantages in the current competitive atmosphere such as reducing short manufacturing cycle time and maintaining the production flexibility, thereby achieving several feasible process plans. An N-person non-co-operative game with complete information is proposed and a mathematical model has been developed to generate the payoff functions. To be part of a game, we divided the game into two sub-games such as games to address sub-game (GASG) and games to solve sub-game (GSSG) which try to interact with each other and achieve the Nash equilibrium (NE). Consequently, a hybrid dynamic-DNA (HD-DNA) based evolutionary algorithm approach has been developed for more effective solutions of the game and also for finding the perfect NE points. The objective of this game is to generate the optimal process plans to minimise the makespan. Finally, three cases having different job complexities are presented to demonstrate the feasibility of the approach. The proposed algorithm is validated and results are analysed to benefit the manufacturer.
Keyword:
networked manufacturing
Nash equilibrium
payoff
makespan
process planning
scheduling
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
7.3
论文数:
1.1W
被引数:
3.7W
机构
引用论文
Hybrid Electrical/Optical Switch Architectures for Training Distributed Deep Learning in Large-Scale

