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Mutation Adaptive Genetic Algorithm for Constrained Capacity Planning Problems in Operations Research

Priboi, Florin Alexandru (2025) Mutation Adaptive Genetic Algorithm for Constrained Capacity Planning Problems in Operations Research.

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Abstract:Having the best planning for business processes is essential for maximising profit and reducing production times. The problem arises when a large number of variables, for instance, the number of products, workers, locations, or production times, have to be taken into account, as such a combinatorial problem is computationally expensive. In the past, Genetic Algorithms (GA) have been proposed for solving these optimisation problems, and they have yielded great results. This study explores the application of GAs in Opera tions Research and breaks down each design consideration needed to adapt the Standard Genetic Algorithm to solve optimisation problems. With these requirements in mind, a new Mutation Adaptive Genetic Algorithm (MAGA) is proposed.
Item Type:Essay (Bachelor)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:54 computer science
Programme:Computer Science BSc (56964)
Link to this item:https://purl.utwente.nl/essays/107279
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