Unified Genetic Algorithm Approach for Solving Flexible Job-Shop Scheduling Problem

Unified Genetic Algorithm Approach for Solving Flexible Job-Shop Scheduling Problem

This paper proposes a novel genetic algorithm (GA) approach that utilizes a multichromosome to solve the flexible job-shop scheduling problem (FJSP), which involves two kinds of decisions: machine selection and operation sequencing. Typically, the former is represented by a string of categorical val...

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Bibliographic Details
Main Authors: Jin-Sung Park, Huey-Yuen Ng, Tay-Jin Chua, Yen-Ting Ng, Jun-Woo Kim
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Applied Sciences
Subjects:
flexible job-shop scheduling problem
combinatorial optimization
genetic algorithm
candidate order-based genetic algorithm
multichromosome
Online Access:https://www.mdpi.com/2076-3417/11/14/6454

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