Evolutionary Approaches to Solve an Integrated Lot Scheduling Problem in the Soft Drink Industry

Abstract

This paper proposes two evolutionary approaches as procedures 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 first approach to solve the SITLSP is a multi-population genetic algorithm (GA) with a hierarchical ternary tree structure for populations. The second approach is a memetic algorithm (MA) that extends the GA approach through the inclusion of a local search procedure. The computational study reported reveals that those methods are an effective alternative to solve real-world instances of the SITLSP.