Batch scheduling of jobs with identical process times on flexible flow lines

Abstract

We consider a batch scheduling problem for flexible flow lines. A number of jobs have to be scheduled, and each job belongs to a specific product type. Setup costs are incurred when changing a machine from one product type to another. On each stage, all jobs have the same process time. The objective is to minimize setup costs and the mean flow time. We identify an analogy to a pallet-loading problem and present a solution approach that consists of two nested genetic algorithms. The heuristic solves realistic problem sizes in a relatively short amount of time. It can be adjusted by a lookahead-parameter that enables a human planner to effectively manage the trade-off between the two objectives.