—Supply chain is an integral part of the operations
management and became a significant concept for overall
profitability of industrial scenario. It consists of several levels
in which material flows through various stages to reach the
end customer. A three level supply chain consists of a
manufacturer, distributor and retailer, who are the cost
bearers. It is necessary to have a coordinated approach
between the tiers so that the chain is timed accurately for least
inventory and minimum cost consequently maximum profits.
In this paper, we consider a coordinated three echelon supply
chain with a single manufacturer supplying a single type of
product to single distributor and then to a single retailer. A
mathematical model is developed for the coordinated supply
chain under consideration and it is solved using Particle
Swarm Optimization (PSO) algorithm and Genetic Algorithm
(GA) for optimal values of decision variables and objective
function. A numerical example is posed and the results
obtained herein are compared for these techniques.
—Genetic algorithm, multi-echelon inventory
problem, particle swarm optimization, supply chain.
A. Gupta, V. Narayan, and A. Raj are with Mechanical engineering
student in Vellore institute of technology, Vellore-632014, Tamil Nadu,
India (email: email@example.com; firstname.lastname@example.org;
Harsh is with Computer science engineering student in Vellore institute
of technology, Vellore-632014, Tamil Nadu, India (email:
D. Nagaraju is with Manufacturing Division, School of Mechanical and
Building Sciences, VIT University, Vellore-632014, Tamil Nadu, India
Cite:Anshul Gupta, Vishal Narayan, Abhishek Raj, Harsh, and D.Nagaraju, "A Comparative Study of Three Echelon Inventory Optimization using Genetic Algorithm and Particle Swarm Optimization.," International Journal of Trade, Economics and Finance vol.3, no.3, pp. 205-208, 2012.