Modular sequence optimization with hybrid genetic algorithm

Higher customer requirements and increasing competitive pressure lead to a growing number of variants and smaller batch sizes in manufacturing. As a result, companies have to deal with challenges of small series manufacturing. A unidimensional set-up optimization cannot provide a satisfying solution. At the same time, production system-specific control algorithms are usually complex and require constant adaptation as customer requirements change continuously. To address these issues, this paper presents a hybrid genetic algorithm which allows modular sequence optimization in production scheduling. Hybrid elements are used to reach a high solution quality within a short runtime.