Joint Replenishment Problem with Multisupplier using Hybrid Genetic Algorithm(<Special English Issue>Global Supply Chain Management)

Abstract

The joint replenishment problem (JRP) involves determining a replenishment policy that minimizes the total cost of replenishing multiple items from a single supplier. In this paper, we propose a new approach for the JRP where items are procured from multisupplier. In solution algorithms, the Genetic Algorithm (GA) and the Simulated Annealing (SA) are cooperatively used. In this method, the convergence of GA is improved by introducing the probability of SA as the criterion for acceptance of new trial solution. We use genetic algorithm for this problem. The purpose of the proposed algorithm in this paper is to minimize the total relevant costs per unit time. The effectiveness of the proposed algorithm is shown through a simulation study.