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Abstract
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| In this paper, we aim to optimize an aluminum casting process to create parts for the automotive sector. The company has six aluminum injection molding machines to produce different parts. There are a total of 81 injection molds for 160 diff erent types of parts, including molds for a single part, two or even three di erent parts. We must account for constraints regarding which molds can be used in each machine, mold changes (up to four a day, which may be non-simultaneous mold or not coincide with worker shift changes), stock of parts, time set aside for machine breakdowns and scheduled machine maintenance processes. The objectives for a two-week planning period are to maximize accumulated demand satisfaction in the two weeks of the di fferent pieces, minimize the delay in parts production with respect to the specified delivery date, minimize energy costs (electricity and gas consumption) and minimize the total number of mold changes performed. A heuristic is used to derive an initial feasible solution. Simulated annealing is then applied to derive the optimal solution. To do this, di fferent neighborhood definitions are created based on the total or partial elimination or introduction of injections or on injection mold changes, whose use dynamically varies throughout the search process. | |
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International
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Si |
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Congress
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29th European Conference on Operational Research |
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960 |
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Place
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Valencia, España |
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Reviewers
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No |
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ISBN/ISSN
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978-84-09-02938-9 |
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Start Date
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08/07/2018 |
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End Date
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11/07/2018 |
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From page
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334 |
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To page
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334 |
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Conference handbook |