Advancing Genetic Programming for Learning Scheduling Heuristics

About this item

Title

Advancing Genetic Programming for Learning Scheduling Heuristics

Content partner

Victoria University of Wellington

Collection

Open Access Victoria University of Wellington

Description

<strong>Dynamic flexible job shop scheduling (DFJSS) has attracted a lot of attention from both academics and industries because of its widespread industrial impact in the real world. The main challenge in DFJSS involves simultaneous machine assignment and operation sequencing under dynamic environments such as new jobs arriving over time. Among the existing methods, scheduling heuristics stand out as effective approaches widely employed because of their simplicity and real-time responsivenes...

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Format

Research paper

Research format

Scholarly text / Thesis

Thesis level

Doctoral

Date created

2024

Creator

Meng Xu

URL

https://figshare.com/articles/thesis/Advancing_Genetic_Programming_for_Learning_Scheduling_Heuris...

Related subjects

Flexible manufacturing systems / Manufacturing management / Genetic programming / Scheduling heuristic / Job shop scheduling / School: School of Engineering and Computer Science / Industrial machinery and equipment / Autonomous and robotic systems / Degree Discipline: Computer Science / Degree Name: Doctor of Philosophy / Degree Level: Doctoral

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