Abstract
We present a novel genetic algorithm for the Robotic Cell Problem with controllable processing times. This challenging problem arises in an automated production cell that consists of m consecutive machines as well as a material handling robot. The problem requires finding the operations processing times, job assignment, and robot movements. The objective is to minimize the makespan subject to a budget constraint. We describe a free-slack-based genetic algorithm for the linear resource consumption case. We present the results of a computational study and we provide evidence that the proposed algorithm consistently outperforms MIP-based heuristics from the literature.
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Al-Salem, M., Haouari, M., Kharbeche, M., Khallouli, W. (2016). A Free-Slack-Based Genetic Algorithm for the Robotic Cell Problem with Controllable Processing Times. In: Rabadi, G. (eds) Heuristics, Metaheuristics and Approximate Methods in Planning and Scheduling. International Series in Operations Research & Management Science, vol 236. Springer, Cham. https://doi.org/10.1007/978-3-319-26024-2_4
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DOI: https://doi.org/10.1007/978-3-319-26024-2_4
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