scholarly journals Decentralized Genetic Algorithm for Dynamic Plant Layout Problem

2019 ◽  
Vol 677 ◽  
pp. 052080
Author(s):  
Weidong Liang ◽  
Dianjun Fang
Keyword(s):  
Genetic Algorithm ◽  
Layout Problem ◽  
Plant Layout ◽  
Dynamic Plant

A hybrid genetic algorithm for the dynamic plant layout problem

2003 ◽  
Vol 86 (2) ◽  
pp. 107-120 ◽  
Author(s):  
Jaydeep Balakrishnan ◽  
Chun Hung Cheng ◽  
Daniel G Conway ◽  
Chun Ming Lau
Keyword(s):  
Genetic Algorithm ◽  
Hybrid Genetic Algorithm ◽  
Layout Problem ◽  
Plant Layout ◽  
Dynamic Plant

A Tabu-Search Heuristic for the Dynamic Plant Layout Problem

1997 ◽  
Vol 9 (4) ◽  
pp. 374-384 ◽  
Author(s):  
Bharat K. Kaku ◽  
Joseph B. Mazzola
Keyword(s):  
Tabu Search ◽  
Layout Problem ◽  
Plant Layout ◽  
Search Heuristic ◽  
Dynamic Plant

scholarly journals An improved pair-wise exchange heuristic for the dynamic plant layout problem

2000 ◽  
Vol 38 (13) ◽  
pp. 3067-3077 ◽  
Author(s):  
Jaydeep Balakrishnan ◽  
Chun Hung Cheng ◽  
Daniel G. Conway
Keyword(s):  
Layout Problem ◽  
Plant Layout ◽  
Dynamic Plant ◽  
Exchange Heuristic

Solving the Dynamic Plant Layout Problem using a new hybrid meta-heuristic algorithm

2006 ◽  
Vol 4 (5/6) ◽  
pp. 286 ◽  
Author(s):  
Jose M. Rodriguez ◽  
F. Chris MacPhee ◽  
David J. Bonham ◽  
Virendrakumar C. Bhavsar
Keyword(s):  
Heuristic Algorithm ◽  
Layout Problem ◽  
Plant Layout ◽  
Dynamic Plant

scholarly journals An Evolutionary Multiagent Framework for Multiobjective Optimization

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Zihui Zhang ◽  
Qiaomei Han ◽  
Yanqiang Li ◽  
Yong Wang ◽  
Yanjun Shi
Keyword(s):  
Genetic Algorithm ◽  
Multiobjective Optimization ◽  
Evolutionary Algorithm ◽  
Layout Optimization ◽  
Layout Problem ◽  
System Decomposition ◽  
System Memory ◽  
Satellite Equipment ◽  
Complete Solutions ◽  
Evolutionary Mode

This article proposes an evolutionary multiagent framework of the co-operative co-evolutionary multiobjective model (CCMO-EMAS), specifically for equipment layout optimization in engineering. In this framework, each agent is set in a multiobjective cooperative co-evolutionary mode along with the algorithms and corresponding settings. In each iteration, agents are executed in turn, and each agent optimizes a subpopulation from system decomposition. Additionally, the collaboration mechanism is addressed to build complete solutions and evaluate individuals in the co-operative co-evolutionary algorithm. Each subpopulation is optimized once, and the corresponding agent is evaluated based on the improvement of the system memory. Moreover, the agent team is also evolved through an elite genetic algorithm. Finally, the proposed CCMO-EMAS framework is verified in a multimodule satellite equipment layout problem.

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