A method to evaluate downstream and upstream information sharing using the genetic algorithm

This paper deals with four scenarios of sharing upstream and downstream information simultaneously in supply chains. Replenishment leadtime is the upstream information studied in this work and demand information is the downstream one. We propose a system cost formulation for two echelon (a depot and several retailers) and multiproducts supply chain. We focused our study on a centralized system case. In our formulation, we consider holding, ordering, penalty and transportation costs. Then, we use a genetic algorithm in order to approximate the optimal echelon inventory position at depot which minimizes the system cost. Our approach is illustrated by some numerical experiments.