A Genetic Algorithm Approach to Solve the Synchronized and Integrated Two-Level Lot Sizing and Scheduling Problem

This paper proposes a Genetic Algorithm approach to solve the Synchronized and Integrated Two-Level Lot Sizing and Scheduling Problem (SITLSP). This problem can be found in some industrial settings, mainly soft drink companies, where the production process involves two interdependent levels with decisions concerning raw material storage and soft drink bottling. The challenge is to simultaneously determine the lot sizing and scheduling of raw materials in tanks and soft drinks in the bottling lines, where setup costs and times depend on the previous items stored and bottled. A Multi-Population Genetic Algorithm approach with a particular representation of solutions for individuals and a hierarchical ternary tree structure for populations is proposed. The computational study reported here reveals that this procedure is the only viable method to solve real-world and industrial instances, and it gives better results on the medium problems than an exact approach.