Hybrid biogeography-based optimization for solving vendor managed inventory system

Abstract

In the modern era of industrialization and globalization, distribution and control of goods are essential aspects for multinational corporations and strategic partners. Vendor managed inventory (VMI) is one of the well-known strategies of merchandizing between supplier and retailer. In this paper, we consider different number of suppliers and retailers to perform business under VMI system and formulate three: single-supplier and single-retailer, single-supplier and multi-retailer, and multi-supplier and multi-retailer VMI systems. The objective is to minimize the total cost of VMI system. Since it is a non-linear integer programming problem, this paper proposes a novel hybrid biogeography-based optimization algorithm to solve it. We enhance the proposed algorithm by embedding stochastic fractal search (SFS) in biogeography-based optimization (BBO). SFS algorithm is a newly developed powerful evolutionary algorithm to find global optimum much faster and efficiently. The diffusion process of SFS improved the exploitation ability of search in BBO. Our proposed algorithm is applied on all three versions of VMI systems under different constraints. We have considered suitable input data for all the different problems and obtained the results. By comparison, we show that the results outperformed for all VMI systems.