A Hybrid Search Using Genetic Algorithms and Random-Restart Hill-Climbing for Flexible Job Shop Scheduling Instances with High Flexibility

This work presents a novel hybrid algorithm called GA-RRHC based on genetic algorithms (GAs) and a random-restart hill-climbing (RRHC) algorithm for the optimization of the flexible job shop scheduling problem (FJSSP) with high flexibility (where every operation can be completed by a high number of...

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Detaylı Bibliyografya
Asıl Yazarlar:	Nayeli Jazmin Escamilla-Serna, Juan Carlos Seck-Tuoh-Mora, Joselito Medina-Marin, Irving Barragan-Vite, José Ramón Corona-Armenta
Materyal Türü:	Artigo
Dil:	Inglês
Baskı/Yayın Bilgisi:	MDPI AG 2022-08-01
Seri Bilgileri:	Applied Sciences
Konular:	flexible job shop scheduling instances genetic operators local search methods cellular automata
Online Erişim:	https://www.mdpi.com/2076-3417/12/16/8050
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A Hybrid Search Using Genetic Algorithms and Random-Restart Hill-Climbing for Flexible Job Shop Scheduling Instances with High Flexibility

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