Artificial bee colony for inventory routing problem with backordering - Moin, N.H.; Halim, H.Z.A. (2014)
This paper addresses the inventory routing problem with backordering (IRPB) with a one-tomany distribution network, consisting of a single depot and multiple customers for a specified planning horizon. A fleet of homogeneous vehicles delivers a single product to fulfill the customers demand over the planning horizon. We assume that the depot has sufficient supply of items that can cover all the customers' demands for all periods. The backorder situation considered here is when the backorder decision either unavoidable (insufficient vehicle capacity) or more economical (savings in the coordinated transportation cost are higher than the backorder cost). The objective of IRPBis to minimize the overall cost such that transportation cost, inventory cost and backorder cost is optimal. We propose a metaheuristic method, Artificial Bee Colony (ABC) to solve the IRPB.The ABCalgorithm is a swarm based heuristics which simulates the intelligent foraging behaviour of a honey bee swarm and sharing that information of the food sources with the bees in the nest. The bees are classified into three agents: the employed bee which carries the information about the food source, the onlooker bee watching the dance of the employed bees within the hive and making the decision to choose a food source based on the dances, and the scout bee, performing random search for the food sources. We modify the standard ABC algorithm by incorporating the inventory and backorder information and, a new inventory updating mechanism incorporating the forward and backward transfers. The modification also being made in the selection mechanism by the onlooker bees based on the waggle dance performed by the employed bees. We run the algorithm on a set of benchmark problems and the results are very encouraging.