Solving inventory - routing problem with backordering using artificial bee colony: Case study of GHTK Company

Abstract

The main interest in this thesis is solving Inventory Routing Problem with Backordering (IRPB) by using Artificial Bee Colony. Inventory Routing Problem (IRP) is the combination of two closely interrelated logistical decisions arising in distribution planning contexts, inventory allocation and vehicle routing. The considered network is one-to-many distribution network which consists a single depot and multiple post-offices. The depot is responsible to deliver a single product to post-offices and manage their inventory, assigns delivery routes efficiently; also, the depot is assumed to have enough supply to cover all the demand throughout the planning horizon. Backorder decision are allowed if it shows economic result. The objective of IRPB is minimize the total supply chain cost, which is the sum of inventory cost, backordering cost and transportation cost. Artificial Bee Colony (ABC) is used to obtain a more effective solutions which is improve the routing and inventory updating mechanism. The research in this paper is inspired by the case of GHTK company; the mathematical model is modified based on Abdelmaguid and Dessouky (2005), Abdelmaguid, Dessouky, Ordonez (2008) and consulted from Model 2 from thesis of Bui Le Hong Nhung (2018); the ABC algorithm is studied based on Karaboga (2005) and Halim and Moin (2014). Keywords: Inventory Routing Problem with Backordering, Artificial Bee Colony, Vehicle Routing Problem, Inventory Control Management, Vendor Managed Inventory.