A genetic algorithm for warehouse multi-objective optimisation

摘要

The rapid increase of warehouse use demands automated management services in order to make decisions for all tasks concerned. These decisions must ensure optimised usage of resources, which leads to cost reduction and better customer service. A major consideration is the way the warehouse area, which consists of different storage types and similar product groups, is exploied. The optimisation fo the warehouse's occupied area is the target of replenishment, which is essentially a constrained placement problem. In this paper, a genetic algorithm with revised operators is developed. This algorithm is applied to real warehouse data and results show that it produces successful replenishments in a complex environment where many criteria have to be considered and met to some user-defined extent.