Flexible Job Shop Scheduling Optimization Using Genetic Algorithm For Handling Dynamic Factors

Flexible Job Shop Scheduling Optimization Using Genetic Algorithm For Handling Dynamic Factors

This research introduces the Genetic Adaptive Scheduling System (GASS), a novel framework designed to optimize scheduling in Flexible Job Shop Scheduling Problems (FJSP). Due to its complexity, FJSP presents significant challenges stemming from machine flexibility, dynamic routing, and operation pr...

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Bibliographic Details
Main Authors: Masmur Tarigan, Ford Lumban Gaol, Tuga Mauritsius, Widodo Budiharto
Format: Article
Language:English
Published: Yayasan Pendidikan Riset dan Pengembangan Intelektual (YRPI) 2025-06-01
Series:Journal of Applied Engineering and Technological Science
Subjects:
Flexible Job Shop Scheduling
Genetic Adaptive Scheduling System
Dynamic Scheduling Optimization
Manufacturing Process Efficiency
Real-Time Production Scheduling
Online Access:http://journal.yrpipku.com/index.php/jaets/article/view/5784
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