Supply Chain Freight Cost Optimization Algorithms and Swarm Intelligence Techniques: A Perspective

Authors

  • Jignasu Mahidhareeya Computer Department, Atmiya Institute of Technology and Science, Rajkot, Gujarat, India
  • Kruti Khalpada Asst. Prof., Computer Department, Atmiya Institute of Technology and Science, Rajkot, Gujarat, India

Keywords:

Vogel’s Approximation Method (VAM), Ant colony optimization (ACO), artificial bee colony algorithm (ABC), Freight Cost (FC), Supply Chain Management (SCM)

Abstract

Optimal distribution of Finish Goods (FG) is key aspect in Supply Chain Management (SCM) for
maximizing gross profit and dispatch adherence. Overall Freight Cost optimization performs major role in
logistic and factory allocation planning. Vogel Approximation Method (VAM) is unit cost penalty method used
to allocate supply to demand and to map factories with depots using Linear Programming (LP). Swarm
Intelligence Technique derived from behavior of social insect’s colony is in current research to use with Supply
Chain Management (SCM) cost optimization using Artificial Intelligence.

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Published

2016-11-25

How to Cite

Jignasu Mahidhareeya, & Kruti Khalpada. (2016). Supply Chain Freight Cost Optimization Algorithms and Swarm Intelligence Techniques: A Perspective. International Journal of Advance Research in Engineering, Science & Technology, 3(11), 90–93. Retrieved from https://ijarest.org/index.php/ijarest/article/view/1108

Issue

Vol. 3 No. 11 (2016): Volume: 03, Issue: 11 - November, 2016.

Section

Articles