A New Algorithm for Vehicle Routing Problem in Reverse Logistics
Product recovery has become significant business strategies to increase a competitive edge in business and also in
the society. Parts from discarded products due to rapid advancement and post-consumer products before & after end-of-life
(EOL) are recovered to reduce landfill waste and to have become a part of circular economy. Product recovery is made
possible with the help of Closed-loop supply chain (CLSC). This paper concentrates on multi-period, multi-product, and
multi-echelon Closed Loop Green Supply Chain (CLGSC) network. A bi-objective (cost and emission) Mixed Integer Linear
Programming (MILP) model has been formulated for the network and has been optimized using Goal Programming
approach and Genetic Algorithm. Results are discussed for providing some managerial insights of the model.
Keywords - Bi-Objective, CLGSC, Product Recovery, Goal Programming, Emission, Vehicle Routing.