An Efficient Iterated Local Search Algorithm to Solve the Operational Workload Imbalance Problem

Abstract

To stay competitive and preserve high service levels for customers, the focus of warehouses in today's supply chain is on fast and timely delivery of smaller and more frequent orders. To keep up with competitors, companies accept late orders from customers, which results in additional pressure for order picking operations. Specifically, more orders need to be picked and sorted in shorter and more flexible time windows, which often results in workload peaks during the day. The objective of this study is to formulate and solve the operational workload imbalance problem in parallel zone order picking systems. An iterated local search algorithm is provided to solve the planning problem. Solving the operational workload imbalance problem results in a more stable order picking process and overall productivity improvements for the total warehouse operations.