Decision Making to Select the Best Order Quantity (BOQ) from Supplier using Genetic Algorithm

Abstract

Manufacturers need to have a good supply chain management system in order to achieve low inventory levels, short lead times and adjustability to meet customer demands at minimal total operation cost. The most important drawback of existing methods used to minimize inventory costs as Just-in-time (JIT) methodology or to minimize transportation and order costs as Economic Order Model (EOQ). This minimization strategy may not be able to give the best order quantity because of the relationship between inventory cost and transportation cost, In this paper, we used genetic algorithm (GA) to reduce the inventory and transportation costs together to determine the Best Order Quantity (BOQ). The main advantage of this new method, it is covers pull system, push systems, short planning horizon, and long planning horizon.