Ant-based distributed optimization for supply chain management

被引：0
|
作者：
Silva, CA [1 ]
Sousa, JM [1 ]
Runkler, T [1 ]
da Costa, JMG [1 ]
机构：
[1] Univ Tecn Lisboa, Dep Mech Engn, Inst Super Tecn, Lisbon, Portugal
来源：
ADAPTIVE AND NATURAL COMPUTING ALGORITHMS | 2005年
关键词：
D O I：
10.1007/3-211-27389-1_86
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Multi-agent systems are the best approach for an efficient supply chain management. However, the control of each sub-system in a supply-chain is a complex optimization problem and therefore the agents have to include powerful optimization resources along with the communication capacities. This paper presents a new methodology for supply-chain management, the distributed optimization based on ant colony optimization, where the concepts of multi-agent systems and metaheuristics are merged. A simulation example, with the logistic and the distribution sub-systems of a supply-chain, shows how the distributed optimization outperforms a centralized approach.
引用
收藏
页码：357 / 360
页数：4
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