Scheduling parallel-batching processing machines problem with learning and deterioration effect in fuzzy environment
Rui Wang, Zhaohong Jia, Kai Li
Abstract
In this paper, a problem of scheduling jobs with different sizes and fuzzy processing times (FPT) on non-identical parallel batch machines to minimize makespan is investigated. Moreover, the processing time (PT) of each batch is subject to the location-based learning and total-PT-based deterioration effect. Since this is an NP-hard combinatorial optimization problem, an improved intelligent algorithm based on fruit fly optimization algorithm (IFOA) is proposed. To verify the performance of the algorithm, the IFOA is compared with three state-of-the-art algorithms. The comparative results demonstrate that the proposed IFOA outperforms the other compared algorithms.
Topics & Concepts
Job shop schedulingComputer scienceScheduling (production processes)Mathematical optimizationFuzzy logicBatch processingArtificial intelligenceMathematicsEmbedded systemRouting (electronic design automation)Programming languageScheduling and Optimization AlgorithmsAdvanced Manufacturing and Logistics OptimizationOptimization and Packing Problems