Effective allocation of customers to distribution centres: A multiple ant colony optimization approach

Tung Sun Chan, Niraj Kumar

Research output: Journal article publicationJournal articleAcademic researchpeer-review

29 Citations (Scopus)


The global and competitive business environment has identified the importance of a quick and efficient service towards the customers in the past few decades. Distribution centre (DC) plays an important role in maintaining the uninterrupted flow of goods and materials between the manufacturer and customers. The performance of the supply chain network can be easily improved by an effective or balanced allocation of customers to DCs. Improper or unbalanced allocation of customers can lead to the under- or overutilization of facilities and can further deteriorate the customer service. Performance of the DC can be judged on the basis of its ability to provide the right goods, at the right time and at the right place. The lead time or transit time to deliver the goods to the customers is an important parameter for the measuring the efficiency and effectiveness of a particular DC in a supply chain. In this paper, a multiple ant colony optimization (MACO) approach is discussed in an effort to design a balanced and efficient supply chain network that maintains the best balance of transit time and customers service. The focus of this paper is on the effective allocation of the customers to the DCs with the two-fold objective of minimization of the transit time and degree of imbalance of the DCs. MACO technique is a modified form of the traditional ant colony system, where multiple ant colonies cooperate with each other to find the best possible customer allocation pattern for the DC. The proposed technique shows better performance because of its nature of considering both positive and negative feedback in search of optimum or near-optimum results. The developed algorithm based on the proposed approach is tested on a real practical problem and the results are discussed in this paper.
Original languageEnglish
Pages (from-to)1-12
Number of pages12
JournalRobotics and Computer-Integrated Manufacturing
Issue number1
Publication statusPublished - 1 Feb 2009
Externally publishedYes


  • Ant colony system
  • Balanced allocation
  • Distribution centre
  • Supply chain network

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • General Mathematics
  • Computer Science Applications
  • Industrial and Manufacturing Engineering


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