A Reinforcement Learning Approach for the Flexible Job Shop Scheduling Problem

Yailen Martinez Jimenez; Ann Nowe; Suarez Juliett; Bello Rafael

A Reinforcement Learning Approach for the Flexible Job Shop Scheduling Problem

Yailen Martinez Jimenez, Ann Nowe, Suarez Juliett, Bello Rafael

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › Research

15 Citations (Scopus)

Abstract

In this work we present a Reinforcement Learning approach for the Flexible Job Shop Scheduling problem. The proposed approach
follows the ideas of the hierarchical approaches and combines learning and optimization in order to achieve better results. Several problem instances were used to test the algorithm and to compare the results with those reported by previous approaches.

Original language	English
Title of host publication	Proc. Fifth International Conference on Learning and Intelligent Optimization (LION5)
Editors	Carlos A. Coello Coello, Xin Yao
Publisher	Lecture Notes in Computer Science, Springer
Pages	253-262
Number of pages	10
Volume	6683
ISBN (Print)	978-3-642-25565-6
Publication status	Published - 2011
Event	Unknown - Duration: 1 Jan 2011 → …

Publication series

Name	Proc. Fifth International Conference on Learning and Intelligent Optimization (LION5)

Conference

Conference	Unknown
Period	1/01/11 → …

Bibliographical note

Carlos A. Coello Coello, Xin Yao

Keywords

scheduling
Reinforcement Learning
Flexible Job SHop

Cite this

Martinez Jimenez, Y., Nowe, A., Juliett, S., & Rafael, B. (2011). A Reinforcement Learning Approach for the Flexible Job Shop Scheduling Problem. In C. A. C. Coello, & X. Yao (Eds.), Proc. Fifth International Conference on Learning and Intelligent Optimization (LION5) (Vol. 6683, pp. 253-262). (Proc. Fifth International Conference on Learning and Intelligent Optimization (LION5)). Lecture Notes in Computer Science, Springer.

Martinez Jimenez, Yailen ; Nowe, Ann ; Juliett, Suarez ; Rafael, Bello. / A Reinforcement Learning Approach for the Flexible Job Shop Scheduling Problem. Proc. Fifth International Conference on Learning and Intelligent Optimization (LION5). editor / Carlos A. Coello Coello ; Xin Yao. Vol. 6683 Lecture Notes in Computer Science, Springer, 2011. pp. 253-262 (Proc. Fifth International Conference on Learning and Intelligent Optimization (LION5)).

@inproceedings{486638773d8149b6b517f23d787d6511,

title = "A Reinforcement Learning Approach for the Flexible Job Shop Scheduling Problem",

abstract = "In this work we present a Reinforcement Learning approach for the Flexible Job Shop Scheduling problem. The proposed approach follows the ideas of the hierarchical approaches and combines learning and optimization in order to achieve better results. Several problem instances were used to test the algorithm and to compare the results with those reported by previous approaches.",

keywords = "scheduling, Reinforcement Learning, Flexible Job SHop",

author = "{Martinez Jimenez}, Yailen and Ann Nowe and Suarez Juliett and Bello Rafael",

note = "Carlos A. Coello Coello, Xin Yao; null ; Conference date: 01-01-2011",

year = "2011",

language = "English",

isbn = "978-3-642-25565-6",

volume = "6683",

series = "Proc. Fifth International Conference on Learning and Intelligent Optimization (LION5)",

publisher = "Lecture Notes in Computer Science, Springer",

pages = "253--262",

editor = "Coello, {Carlos A. Coello} and Xin Yao",

booktitle = "Proc. Fifth International Conference on Learning and Intelligent Optimization (LION5)",

}

Martinez Jimenez, Y , Nowe, A, Juliett, S & Rafael, B 2011, A Reinforcement Learning Approach for the Flexible Job Shop Scheduling Problem. in CAC Coello & X Yao (eds), Proc. Fifth International Conference on Learning and Intelligent Optimization (LION5). vol. 6683, Proc. Fifth International Conference on Learning and Intelligent Optimization (LION5), Lecture Notes in Computer Science, Springer, pp. 253-262, Unknown, 1/01/11.

A Reinforcement Learning Approach for the Flexible Job Shop Scheduling Problem. / Martinez Jimenez, Yailen ; Nowe, Ann; Juliett, Suarez; Rafael, Bello.

Proc. Fifth International Conference on Learning and Intelligent Optimization (LION5). ed. / Carlos A. Coello Coello; Xin Yao. Vol. 6683 Lecture Notes in Computer Science, Springer, 2011. p. 253-262 (Proc. Fifth International Conference on Learning and Intelligent Optimization (LION5)).

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › Research

TY - GEN

T1 - A Reinforcement Learning Approach for the Flexible Job Shop Scheduling Problem

AU - Martinez Jimenez, Yailen

AU - Nowe, Ann

AU - Juliett, Suarez

AU - Rafael, Bello

N1 - Carlos A. Coello Coello, Xin Yao

PY - 2011

Y1 - 2011

N2 - In this work we present a Reinforcement Learning approach for the Flexible Job Shop Scheduling problem. The proposed approach follows the ideas of the hierarchical approaches and combines learning and optimization in order to achieve better results. Several problem instances were used to test the algorithm and to compare the results with those reported by previous approaches.

AB - In this work we present a Reinforcement Learning approach for the Flexible Job Shop Scheduling problem. The proposed approach follows the ideas of the hierarchical approaches and combines learning and optimization in order to achieve better results. Several problem instances were used to test the algorithm and to compare the results with those reported by previous approaches.

KW - scheduling

KW - Reinforcement Learning

KW - Flexible Job SHop

M3 - Conference paper

SN - 978-3-642-25565-6

VL - 6683

T3 - Proc. Fifth International Conference on Learning and Intelligent Optimization (LION5)

SP - 253

EP - 262

BT - Proc. Fifth International Conference on Learning and Intelligent Optimization (LION5)

A2 - Coello, Carlos A. Coello

A2 - Yao, Xin

PB - Lecture Notes in Computer Science, Springer

Y2 - 1 January 2011

ER -

Martinez Jimenez Y , Nowe A, Juliett S, Rafael B. A Reinforcement Learning Approach for the Flexible Job Shop Scheduling Problem. In Coello CAC, Yao X, editors, Proc. Fifth International Conference on Learning and Intelligent Optimization (LION5). Vol. 6683. Lecture Notes in Computer Science, Springer. 2011. p. 253-262. (Proc. Fifth International Conference on Learning and Intelligent Optimization (LION5)).

A Reinforcement Learning Approach for the Flexible Job Shop Scheduling Problem

Abstract

Publication series

Conference

Bibliographical note

Keywords

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Cite this