Guide objective assisted particle swarm optimization and its application to history matching

Alan Reynolds; Asaad Abdollahzadeh; David Corne; Michael Andrew Christie; Brian Davies; Glyn Williams

doi:10.1007/978-3-642-32964-7_20

Guide objective assisted particle swarm optimization and its application to history matching

Alan Reynolds, Asaad Abdollahzadeh, David Corne, Michael Andrew Christie, Brian Davies, Glyn Williams

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

2 Citations (Scopus)

Abstract

As is typical of metaheuristic optimization algorithms, particle swarm optimization is guided solely by the objective function. However, experience with separable and roughly separable problems suggests that, for subsets of the decision variables, the use of alternative 'guide objectives' may result in improved performance. This paper describes how, through the use of such guide objectives, simple problem domain knowledge may be incorporated into particle swarm optimization and illustrates how such an approach can be applied to both academic optimization problems and a real-world optimization problem from the domain of petroleum engineering.

Original language	English
Title of host publication	Parallel Problem Solving from Nature - PPSN XII
Subtitle of host publication	12th International Conference, Taormina, Italy, September 1-5, 2012, Proceedings, Part II
Editors	Carlos A. Coello Coello, Vincenzo Cutello, Kalyanmoy Deb, Stephanie Forrest, Giuseppe Nicosia, Mario Pavone
Publisher	Springer
Pages	195-204
Number of pages	10
ISBN (Electronic)	9783642329647
ISBN (Print)	9783642329630
DOIs	https://doi.org/10.1007/978-3-642-32964-7_20
Publication status	Published - Sept 2012
Event	12th International Conference on Parallel Problem Solving From Nature - Taormina, Italy Duration: 1 Sept 2012 → 5 Sept 2012

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	7492
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	12th International Conference on Parallel Problem Solving From Nature
Abbreviated title	PPSN 2012
Country/Territory	Italy
City	Taormina
Period	1/09/12 → 5/09/12

Keywords

Particle swarm optimization (PSO)
Guide objectives
History matching
Reservoir engineering

Access to Document

10.1007/978-3-642-32964-7_20

Cite this

Reynolds, A., Abdollahzadeh, A., Corne, D., Christie, M. A., Davies, B., & Williams, G. (2012). Guide objective assisted particle swarm optimization and its application to history matching. In C. A. Coello Coello, V. Cutello, K. Deb, S. Forrest, G. Nicosia, & M. Pavone (Eds.), Parallel Problem Solving from Nature - PPSN XII: 12th International Conference, Taormina, Italy, September 1-5, 2012, Proceedings, Part II (pp. 195-204). (Lecture Notes in Computer Science; Vol. 7492). Springer. https://doi.org/10.1007/978-3-642-32964-7_20

Reynolds, Alan ; Abdollahzadeh, Asaad ; Corne, David et al. / Guide objective assisted particle swarm optimization and its application to history matching. Parallel Problem Solving from Nature - PPSN XII: 12th International Conference, Taormina, Italy, September 1-5, 2012, Proceedings, Part II. editor / Carlos A. Coello Coello ; Vincenzo Cutello ; Kalyanmoy Deb ; Stephanie Forrest ; Giuseppe Nicosia ; Mario Pavone. Springer, 2012. pp. 195-204 (Lecture Notes in Computer Science).

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title = "Guide objective assisted particle swarm optimization and its application to history matching",

abstract = "As is typical of metaheuristic optimization algorithms, particle swarm optimization is guided solely by the objective function. However, experience with separable and roughly separable problems suggests that, for subsets of the decision variables, the use of alternative 'guide objectives' may result in improved performance. This paper describes how, through the use of such guide objectives, simple problem domain knowledge may be incorporated into particle swarm optimization and illustrates how such an approach can be applied to both academic optimization problems and a real-world optimization problem from the domain of petroleum engineering.",

keywords = "Particle swarm optimization (PSO), Guide objectives, History matching, Reservoir engineering",

author = "Alan Reynolds and Asaad Abdollahzadeh and David Corne and Christie, {Michael Andrew} and Brian Davies and Glyn Williams",

year = "2012",

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language = "English",

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booktitle = "Parallel Problem Solving from Nature - PPSN XII",

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note = "12th International Conference on Parallel Problem Solving From Nature, PPSN 2012 ; Conference date: 01-09-2012 Through 05-09-2012",

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Reynolds, A, Abdollahzadeh, A, Corne, D, Christie, MA, Davies, B & Williams, G 2012, Guide objective assisted particle swarm optimization and its application to history matching. in CA Coello Coello, V Cutello, K Deb, S Forrest, G Nicosia & M Pavone (eds), Parallel Problem Solving from Nature - PPSN XII: 12th International Conference, Taormina, Italy, September 1-5, 2012, Proceedings, Part II. Lecture Notes in Computer Science, vol. 7492, Springer, pp. 195-204, 12th International Conference on Parallel Problem Solving From Nature, Taormina, Italy, 1/09/12. https://doi.org/10.1007/978-3-642-32964-7_20

Guide objective assisted particle swarm optimization and its application to history matching. / Reynolds, Alan; Abdollahzadeh, Asaad; Corne, David et al.
Parallel Problem Solving from Nature - PPSN XII: 12th International Conference, Taormina, Italy, September 1-5, 2012, Proceedings, Part II. ed. / Carlos A. Coello Coello; Vincenzo Cutello; Kalyanmoy Deb; Stephanie Forrest; Giuseppe Nicosia; Mario Pavone. Springer, 2012. p. 195-204 (Lecture Notes in Computer Science; Vol. 7492).

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

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T1 - Guide objective assisted particle swarm optimization and its application to history matching

AU - Reynolds, Alan

AU - Abdollahzadeh, Asaad

AU - Corne, David

AU - Christie, Michael Andrew

AU - Davies, Brian

AU - Williams, Glyn

PY - 2012/9

Y1 - 2012/9

N2 - As is typical of metaheuristic optimization algorithms, particle swarm optimization is guided solely by the objective function. However, experience with separable and roughly separable problems suggests that, for subsets of the decision variables, the use of alternative 'guide objectives' may result in improved performance. This paper describes how, through the use of such guide objectives, simple problem domain knowledge may be incorporated into particle swarm optimization and illustrates how such an approach can be applied to both academic optimization problems and a real-world optimization problem from the domain of petroleum engineering.

AB - As is typical of metaheuristic optimization algorithms, particle swarm optimization is guided solely by the objective function. However, experience with separable and roughly separable problems suggests that, for subsets of the decision variables, the use of alternative 'guide objectives' may result in improved performance. This paper describes how, through the use of such guide objectives, simple problem domain knowledge may be incorporated into particle swarm optimization and illustrates how such an approach can be applied to both academic optimization problems and a real-world optimization problem from the domain of petroleum engineering.

KW - Particle swarm optimization (PSO)

KW - Guide objectives

KW - History matching

KW - Reservoir engineering

U2 - 10.1007/978-3-642-32964-7_20

DO - 10.1007/978-3-642-32964-7_20

M3 - Conference contribution

SN - 9783642329630

T3 - Lecture Notes in Computer Science

SP - 195

EP - 204

BT - Parallel Problem Solving from Nature - PPSN XII

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A2 - Cutello, Vincenzo

A2 - Deb, Kalyanmoy

A2 - Forrest, Stephanie

A2 - Nicosia, Giuseppe

A2 - Pavone, Mario

PB - Springer

T2 - 12th International Conference on Parallel Problem Solving From Nature

Y2 - 1 September 2012 through 5 September 2012

ER -

Reynolds A, Abdollahzadeh A, Corne D, Christie MA, Davies B, Williams G. Guide objective assisted particle swarm optimization and its application to history matching. In Coello Coello CA, Cutello V, Deb K, Forrest S, Nicosia G, Pavone M, editors, Parallel Problem Solving from Nature - PPSN XII: 12th International Conference, Taormina, Italy, September 1-5, 2012, Proceedings, Part II. Springer. 2012. p. 195-204. (Lecture Notes in Computer Science). doi: 10.1007/978-3-642-32964-7_20

Guide objective assisted particle swarm optimization and its application to history matching

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Keywords

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