Variable Neighborhood Search Algorithm for the Variable Cost and Size Bin Packing Problem

Abstract

A company that transports goods to supply customers usually needs to plan the routes that the fleet must follow, since transportation means a high percentage of the value added to goods. The vehicles must be loaded with the products located in the warehouse to fulfill the orders requested by customers. Many enterprises use order batching and picking systems to improve the warehouse management. This chapter describes a novel algorithm based on the methodology of variable neighborhood search for the variable cost and size bin packing problem. This problem considers that the sizes and costs of the bins can be different and there is no correlation between them, which is a sensible assumption for the order batching process in many applications. A series of computational experiments were conducted with a set of hard instances to validate this approach. The results show that the proposed algorithm outperforms the state-of-the-art algorithm, and a statistical hypothesis test is used to support the obtained conclusions.