Genetic Algorithm to Evaluate Downstream and Upstream Information Sharing

Abstract

In this paper, we present an approach to evaluate the information sharing in the supply chain. We propose a study of four scenarios of sharing upstream and downstream information simultaneously. Replenishment lead time is the upstream information studied in this work and demand information is the downstream one. We treat in this context the case of two-echelon (a warehouse and several retailers) and multi-products supply chain. We focus our approach on the centralised decision, in which, the warehouse is the decision maker and his goal is to minimise the system cost independently. In our formulation, we consider a system cost composed of holding, ordering, penalty and transportation costs. Then, we use a Genetic Algorithm in order to approximate the optimal echelon inventory position at the warehouse and optimal allocation quantity of each item from the warehouse to the respective retailer, which minimises the system cost. Our approach is illustrated by some numerical experiments.