A Two-echelon Multi-objective Hybrid Model for Single-Vendor Multiple-Retailer Vendor Management Inventory Problem by using Two Pareto-based Multi-objective Meta-heuristic Algorithms

In this research, a mathematical model for VMI is studied. One goal is to reduce inventory costs in a two-level supply chain, while other goals consider enabling the system and help making decisions in possible demand situations and delivery times, and increasing the level of service and quality, while reducing the costs of increasing the service level. However, to gain more performance in real world problems, constraints exist, e.g. the lack of a low service level, warehouse space, budget, moving capacity, and total integrated discount. In this research, the shipments are assumed to be non-identical, and shortages are considered in two classes: lag and lost sales. Because the achieved model type is of nonlinear integer planning type and an NP-hard problem, meta-heuristic solutions should be used. Regarding two-goal minimization based on reducing total inventory cost, taking possible demand, delivery times, the non-homology of shipments into account, and also shortage and discount, to find the amount of product order and the product shortage level, the achieved model is solved using the required algorithms and tools. Regarding inventory management at two levels of seller and retailer, problems occur containing constraints. Finally, this research aims to obtain inventory management mathematical model by seller in the supply chain in conditions (such as one retailer-one seller, and one seller-multiple retailers), and to provide a solution during uncertainty, non-homology of shipments, when the shortage of lag and lost sales is permitted, and total discount.