Abstract
The distributed optimization paradigm based on Ant Colony Optimization (ACO) is a new management technique that uses the pheromone matrix to exchange information between the different subsystems to be optimized in the supply-chain. This paper proposes the use of the hybrid algorithm Beam-ACO, that fuses Beam-Search and ACO, to implement the same management concept. The Beam-ACO algorithm is used here to optimize the supplying, the distributer and the logistic agents of the supply-chain. Further, this paper implements the concept in a software platform that allows the pheromone matrix exchange through the different agents, using the TCP/IP protocol and data base systems. The results show that the distributed optimization paradigm can still be applied on supply chains where the different agents are optimized by different algorithms and that the use of the Beam-ACO in the supplying agent improves the local and the global results of the supply chain.
Keywords
- Supply Chain
- Schedule Problem
- Logistic System
- Vehicle Route Problem
- Software Platform
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Caldeira, J., Azevedo, R., Silva, C.A., Sousa, J.M.C. (2007). Beam-ACO Distributed Optimization Applied to Supply-Chain Management. In: Melin, P., Castillo, O., Aguilar, L.T., Kacprzyk, J., Pedrycz, W. (eds) Foundations of Fuzzy Logic and Soft Computing. IFSA 2007. Lecture Notes in Computer Science(), vol 4529. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72950-1_78
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DOI: https://doi.org/10.1007/978-3-540-72950-1_78
Publisher Name: Springer, Berlin, Heidelberg
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