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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Principais autores:	Nayeli Jazmin Escamilla-Serna, Juan Carlos Seck-Tuoh-Mora, Joselito Medina-Marin, Irving Barragan-Vite, José Ramón Corona-Armenta
Format:	Artigo
Jezik:	Inglês
Izdano:	MDPI AG 2022-08-01
Serija:	Applied Sciences
Teme:	flexible job shop scheduling instances genetic operators local search methods cellular automata
Online dostop:	https://www.mdpi.com/2076-3417/12/16/8050
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