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  4. Decentralized Supply Chain Optimization via Swarm Intelligence
 
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Decentralized Supply Chain Optimization via Swarm Intelligence

Journal
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Journal Volume
13344 LNCS
ISBN
9783031096761
Date Issued
2022-01-01
Author(s)
Singh, Karan
Liu, Hsin Ping
Phoa, Frederick Kin Hing
SHAU-PING LIN  
Chen-Burger, Yun Heh Jessica
DOI
10.1007/978-3-031-09677-8_36
URI
https://scholars.lib.ntu.edu.tw/handle/123456789/629973
URL
https://api.elsevier.com/content/abstract/scopus_id/85134318126
Abstract
When optimised, supply chains can bring tremendous benefits to all its participants. Supply chains therefore can be framed as a networked optimization problem to which swarm intelligence techniques can be applied. Given recent trends of globalization and e-commerce, we propose a supply chain that uses an open e-commerce business model, where all participants have equal access to the market and are free to trade with each other based on mutually agreed prices and quantities. Based on this model, we improve upon the Particle Swarm Optimization algorithm with constriction coefficient (CPSO), and we demonstrate the use of a new random jump algorithm for consistent and efficient handling of constraint violations. We also develop a new metric called the ‘improvement multiplier’ for comparing the performance of an algorithm when applied to a problem with different configurations.
Subjects
E-commerce | Networked optimization problem | Particle Swarm Optimization | Supply chain | Swarm intelligence
Type
conference paper

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