Making Warehouse Logistics Smart by Effective Placement Strategy Based on Genetic Algorithms

Abstract

Supply chain executives are faced with the challenge of reducing labor costs. Travel time or picking efficiency can easily account for 50% or more of order picking time. If we omit human factor and the technical equipment of the warehouses, picking efficiency is mostly affected by two factors: correct combining orders into a single travel instance and picking orders in batch is the first factor; the second one is a goods placement – the more effective the goods are located, the shorter will be the picking distance for each order or batch of orders. It means that individual orders will be picked faster. Usually to determine the correct location for the goods 3PL’s are using ABC analysis that includes indicators like count of orders, goods turnover, picking rate, weight etc.

Keywords

• logistics
• genetic algorithm
• optimization
• labour costs
• warehouse layout
• location assignment
• picking