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An adaptive penalty guided genetic algorithm for scheduling parallel batch processing machines
Xu, Shubin - In: International journal of applied management science 10 (2018) 3, pp. 247-268
Persistent link: https://www.econbiz.de/10011969051
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A review of the research methodology for the re-entrant scheduling problem
Danping, Lin; Lee, Carman K. M. - In: International journal of production research 49 (2011) 6/8, pp. 2221-2242
Persistent link: https://www.econbiz.de/10008901137
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Throughput optimization for the robotic cell problem with controllable processing times
Al-Salem, Mohammed; Kharbeche, Mohamed - In: RAIRO / Operations research 51 (2017) 3, pp. 805-818
Persistent link: https://www.econbiz.de/10011858837
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Enhanced migrating birds optimization algorithm for the permutation flow shop problem with sequence dependent setup times
Sioud, A.; Gagné, C. - In: European journal of operational research : EJOR 264 (2018) 1, pp. 66-73
Persistent link: https://www.econbiz.de/10011801568
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Cell loading and family scheduling for jobs with individual due dates to minimise maximum tardiness
Süer, Grüsel A.; Ates, Ozan K.; Mese, Emre M. - In: International journal of production research 52 (2014) 19, pp. 5656-5674
Persistent link: https://www.econbiz.de/10010425024
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A global scheduling approach for cycle time control in complex manufacturing systems
Barhebwa-Mushamuka, Félicien; Dauzère-Péres, Stéphane; … - In: International journal of production research 61 (2023) 2, pp. 559-579
Persistent link: https://www.econbiz.de/10013531022
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A hybrid PSO-GA algorithm for job shop scheduling in machine tool production
Liu, Li-Lan; Hu, Rong-Song; Hu, Xiang-Ping; Zhao, Gai-Ping - In: International journal of production research 53 (2015) 19, pp. 5755-5781
Persistent link: https://www.econbiz.de/10011420802
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Workforce rostering for decentrally controlled production systems : a simulation-based optimization framework using a genetic algorithm
Schwemmer, Julia; Günsel, Christian; Kühn, Mathias; … - In: Logistics research 16 (2023) 1, pp. 1-26
Decentral production control plays a crucial role within the paradigm of Industry 4.0. Due to the fast and flexible decisions on allocation and sequencing required by this type of control, there is no baseline production schedule in advance. This creates a dilemma for efficient staff deployment...
Persistent link: https://www.econbiz.de/10014514933
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Distributed job-shop rescheduling problem considering reconfigurability of machines : a self-adaptive hybrid equilibrium optimiser
Mahmoodjanloo, M.; Tavakkoli-Moghaddam, R.; Baboli, A.; … - In: International journal of production research 60 (2022) 16, pp. 4973-4994
Persistent link: https://www.econbiz.de/10013500614
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Hybrid evolutionary optimisation with learning for production scheduling : state-of-the-art survey on algorithms and applications
Lin, Lin; Gen, Mitsuo - In: International journal of production research 56 (2018) 1/2, pp. 193-223
Persistent link: https://www.econbiz.de/10011876295