Enhanced ant colony optimization for inventory routing problem

Lily Wong, Noor Hasnah Moin

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

1 Citation (Scopus)


The inventory routing problem (IRP) integrates and coordinates two important components of supply chain management which are transportation and inventory management. We consider a one-to-many IRP network for a finite planning horizon. The demand for each product is deterministic and time varying as well as a fleet of capacitated homogeneous vehicles, housed at a depot/warehouse, delivers the products from the warehouse to meet the demand specified by the customers in each period. The inventory holding cost is product specific and is incurred at the customer sites. The objective is to determine the amount of inventory and to construct a delivery routing that minimizes both the total transportation and inventory holding cost while ensuring each customer's demand is met over the planning horizon. The problem is formulated as a mixed integer programming problem and is solved using CPLEX 12.4 to get the lower and upper bound (best integer) for each instance considered. We propose an enhanced ant colony optimization (ACO) to solve the problem and the built route is improved by using local search. The computational experiments demonstrating the effectiveness of our approach is presented.

Original languageEnglish
Title of host publication22nd National Symposium on Mathematical Sciences, SKSM 2014
Subtitle of host publicationStrengthening Research and Collaboration of Mathematical Sciences in Malaysia
EditorsIbrahim Mohamed, Wong Kok Bin, Angelina Chin Yan Mui, Loo Tee How
PublisherAmerican Institute of Physics
ISBN (Electronic)9780735413290
Publication statusPublished - 22 Oct 2015
Externally publishedYes
EventNational Symposium on Mathematical Sciences 2014 - Selangor, Malaysia
Duration: 24 Nov 201426 Nov 2014
Conference number: 22nd
https://aip.scitation.org/toc/apc/1682/1 (Proceedings)

Publication series

NameAIP Conference Proceedings
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616


ConferenceNational Symposium on Mathematical Sciences 2014
Abbreviated titleSKSM 2014
Internet address


  • ant colony optimization
  • inventory
  • routing

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