A tabu search algorithm for integrated inventory and vehicle routing problem in one depot and multicustomers distribution system

This research aims to solve Inventory Routing Problem (IRP) by developing two-phase heuristic based on EOQ with power-of-two policy, saving algorithm and tabu search method. The first phase intends to minimize inventory cost while the second phase proposes to minimize transportation cost. We construct fitness function composing of minimizing travelling distance and maximizing vehicle capacity utilization with weighted decision variables. The algorithm mechanism is swapping and applies tabu search to find the optimal solution from possible neighborhood solutions. The effectiveness of developed algorithm is evaluated by comparing the best solution to the initial solution using fitness deviation. The results show that fitness deviation is improved about 22.66% comparing to the fitness value of the initial solution. We perform analysis of variance with randomly generated problems to analyze sensitivity of two factors, number of retailers and setup cost to holding cost ratio. The results show no significant difference of both factors on fitness deviation values at 0.05 significant level.