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

Overview & Synopsis

This paper introduces a Multi-Population Genetic Algorithm as a pro- cedure 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 simultane- ously determine the lot sizing and scheduling of raw materials in tanks and soft drinks in the bottling lines, where setup costs and times de- pend on the previous items stored and bottled. A Multi-Population Ge- netic 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 an alternative to solve real-world instances of the SITLSP.