Research of Pareto-based multi-objective optimization for multi-vehicle assignment problem based on MOPSO

Ai Di-Ming; Zhang Zhe; Zhang Rui; Pan Feng

doi:10.1007/978-3-642-21524-7_2

Research of Pareto-based multi-objective optimization for multi-vehicle assignment problem based on MOPSO

Ai Di-Ming^*, Zhang Zhe, Zhang Rui, Pan Feng

^*Corresponding author for this work

School of Automation

Beijing Institute of Technology

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

1 Citation (Scopus)

Abstract

The purpose of a multi-vehicle assignment problem is to allocate vehicles to complete various missions at different destinations, meanwhile it is required to satisfy all constrains and optimize overall criteria. Combined with MOPSO algorithm, a Pareto-based multi-objective model is proposed, which includes not only the time-cost tradeoff, but also a "Constraint-First-Objective- Next" strategy which handles constraints as an additional objective. Numerical experimental results illustrate that it can efficiently achieve the Pareto front and demonstrate the effectiveness.

Original language	English
Title of host publication	Advances in Swarm Intelligence - Second International Conference, ICSI 2011, Proceedings
Pages	10-16
Number of pages	7
Edition	PART 2
DOIs	https://doi.org/10.1007/978-3-642-21524-7_2
Publication status	Published - 2011
Event	2nd International Conference on Swarm Intelligence, ICSI 2011 - Chongqing, China Duration: 12 Jun 2011 → 15 Jun 2011

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	6729 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	2nd International Conference on Swarm Intelligence, ICSI 2011
Country/Territory	China
City	Chongqing
Period	12/06/11 → 15/06/11

Keywords

Multi-objective Particle swarm optimizer (MOPSO)
Multi-objective vehicle assignment problem
Pareto

Access to Document

10.1007/978-3-642-21524-7_2

Cite this

Di-Ming, A., Zhe, Z., Rui, Z., & Feng, P. (2011). Research of Pareto-based multi-objective optimization for multi-vehicle assignment problem based on MOPSO. In Advances in Swarm Intelligence - Second International Conference, ICSI 2011, Proceedings (PART 2 ed., pp. 10-16). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6729 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-21524-7_2

Di-Ming, Ai ; Zhe, Zhang ; Rui, Zhang et al. / Research of Pareto-based multi-objective optimization for multi-vehicle assignment problem based on MOPSO. Advances in Swarm Intelligence - Second International Conference, ICSI 2011, Proceedings. PART 2. ed. 2011. pp. 10-16 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

@inproceedings{eb8fa7c39f084f59b845915fd396244e,

title = "Research of Pareto-based multi-objective optimization for multi-vehicle assignment problem based on MOPSO",

abstract = "The purpose of a multi-vehicle assignment problem is to allocate vehicles to complete various missions at different destinations, meanwhile it is required to satisfy all constrains and optimize overall criteria. Combined with MOPSO algorithm, a Pareto-based multi-objective model is proposed, which includes not only the time-cost tradeoff, but also a {"}Constraint-First-Objective- Next{"} strategy which handles constraints as an additional objective. Numerical experimental results illustrate that it can efficiently achieve the Pareto front and demonstrate the effectiveness.",

keywords = "Multi-objective Particle swarm optimizer (MOPSO), Multi-objective vehicle assignment problem, Pareto",

author = "Ai Di-Ming and Zhang Zhe and Zhang Rui and Pan Feng",

year = "2011",

doi = "10.1007/978-3-642-21524-7_2",

language = "English",

isbn = "9783642215230",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

number = "PART 2",

pages = "10--16",

booktitle = "Advances in Swarm Intelligence - Second International Conference, ICSI 2011, Proceedings",

edition = "PART 2",

note = "2nd International Conference on Swarm Intelligence, ICSI 2011 ; Conference date: 12-06-2011 Through 15-06-2011",

}

Di-Ming, A, Zhe, Z, Rui, Z & Feng, P 2011, Research of Pareto-based multi-objective optimization for multi-vehicle assignment problem based on MOPSO. in Advances in Swarm Intelligence - Second International Conference, ICSI 2011, Proceedings. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 6729 LNCS, pp. 10-16, 2nd International Conference on Swarm Intelligence, ICSI 2011, Chongqing, China, 12/06/11. https://doi.org/10.1007/978-3-642-21524-7_2

Research of Pareto-based multi-objective optimization for multi-vehicle assignment problem based on MOPSO. / Di-Ming, Ai; Zhe, Zhang; Rui, Zhang et al.
Advances in Swarm Intelligence - Second International Conference, ICSI 2011, Proceedings. PART 2. ed. 2011. p. 10-16 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6729 LNCS, No. PART 2).

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

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AU - Zhe, Zhang

AU - Rui, Zhang

AU - Feng, Pan

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N2 - The purpose of a multi-vehicle assignment problem is to allocate vehicles to complete various missions at different destinations, meanwhile it is required to satisfy all constrains and optimize overall criteria. Combined with MOPSO algorithm, a Pareto-based multi-objective model is proposed, which includes not only the time-cost tradeoff, but also a "Constraint-First-Objective- Next" strategy which handles constraints as an additional objective. Numerical experimental results illustrate that it can efficiently achieve the Pareto front and demonstrate the effectiveness.

AB - The purpose of a multi-vehicle assignment problem is to allocate vehicles to complete various missions at different destinations, meanwhile it is required to satisfy all constrains and optimize overall criteria. Combined with MOPSO algorithm, a Pareto-based multi-objective model is proposed, which includes not only the time-cost tradeoff, but also a "Constraint-First-Objective- Next" strategy which handles constraints as an additional objective. Numerical experimental results illustrate that it can efficiently achieve the Pareto front and demonstrate the effectiveness.

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KW - Multi-objective vehicle assignment problem

KW - Pareto

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Di-Ming A, Zhe Z, Rui Z, Feng P. Research of Pareto-based multi-objective optimization for multi-vehicle assignment problem based on MOPSO. In Advances in Swarm Intelligence - Second International Conference, ICSI 2011, Proceedings. PART 2 ed. 2011. p. 10-16. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-642-21524-7_2

Research of Pareto-based multi-objective optimization for multi-vehicle assignment problem based on MOPSO

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Keywords

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