Decentralized Supply Chain Optimization via Swarm Intelligence

Karan Singh, Hsin Ping Liu, Frederick Kin Hing Phoa*, Shau Ping Lin, Yun-Heh Jessica Chen-Burger

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution


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.

Original languageEnglish
Title of host publicationAdvances in Swarm Intelligence. ICSI 2022
EditorsYing Tan, Yuhui Shi, Ben Niu
Number of pages10
ISBN (Electronic)9783031096778
ISBN (Print)9783031096761
Publication statusPublished - 26 Jun 2022
Event13th International Conference on Swarm Intelligence 2022 - Xi'an, China
Duration: 15 Jul 202219 Jul 2022

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference13th International Conference on Swarm Intelligence 2022
Abbreviated titleICSI 2022


  • E-commerce
  • Networked optimization problem
  • Particle Swarm Optimization
  • Supply chain
  • Swarm intelligence

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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