Analysis of Solution Quality of a Multiobjective Optimization-based Evolutionary Algorithm for Knapsack Problem

Jun He; Yong Wang; Yuren Zhou

doi:10.1007/978-3-319-16468-7_7

Analysis of Solution Quality of a Multiobjective Optimization-based Evolutionary Algorithm for Knapsack Problem

Jun He, Yong Wang, Yuren Zhou

Adran Cyfrifiadureg

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion Cynhadledd › Trafodion Cynhadledd (Nid-Cyfnodolyn fathau)

2 Dyfyniadau (Scopus)

139 Wedi eu Llwytho i Lawr (Pure)

Crynodeb

Multi-objective optimisation is regarded as one of the most promising ways for dealing with constrained optimisation problems in evolutionary optimisation. This paper presents a theoretical investigation of a multi-objective optimisation evolutionary algorithm for solving the 0-1 knapsack problem. Two initialisation methods are considered in the algorithm: local search initialisation and
greedy search initialisation. Then the solution quality of the algorithm is analysed in terms of the approximation ratio.

Iaith wreiddiol	Saesneg
Teitl	Evolutionary Computation in Combinatorial Optimization
Golygyddion	Gabriela Ochoa
Cyhoeddwr	Springer Nature
Tudalennau	74-85
Cyfrol	9026
ISBN (Electronig)	978-3-319-16468-7
ISBN (Argraffiad)	978-3-319-16467-0, 3319164678
Dynodwyr Gwrthrych Digidol (DOIs)	https://doi.org/10.1007/978-3-319-16468-7_7
Statws	Cyhoeddwyd - 15 Maw 2015

Cyfres gyhoeddiadau

Enw	Lecture notes in Computer Science
Cyfrol	9026

Mynediad at Ddogfen

10.1007/978-3-319-16468-7_7

paper-B4-archiveLlawysgrif a gyflwynwyd, 265 KBTrwydded: Aneglur 1

Cysylltiad parhaol

Dolen barhaus

Ffeiliau eraill a chysylltiadau

http://hdl.handle.net/2160/30471

1 Wedi Gorffen

Evolutionary Approximation Algorithms for Optimization: Algorithm design and Complexity Analysis
He, J. (Prif Ymchwilydd)
Engineering & Physical Sciences Research Council
01 Mai 2011 → 31 Hyd 2015
Prosiect: Ymchwil a ariannwyd yn allanol

Dyfynnu hyn

@inproceedings{e1157679be7c4ca08ca4cac0b3f1f2e4,

title = "Analysis of Solution Quality of a Multiobjective Optimization-based Evolutionary Algorithm for Knapsack Problem",

abstract = "Multi-objective optimisation is regarded as one of the most promising ways for dealing with constrained optimisation problems in evolutionary optimisation. This paper presents a theoretical investigation of a multi-objective optimisation evolutionary algorithm for solving the 0-1 knapsack problem. Two initialisation methods are considered in the algorithm: local search initialisation andgreedy search initialisation. Then the solution quality of the algorithm is analysed in terms of the approximation ratio.",

author = "Jun He and Yong Wang and Yuren Zhou",

year = "2015",

month = mar,

day = "15",

doi = "10.1007/978-3-319-16468-7_7",

language = "English",

isbn = "978-3-319-16467-0",

volume = "9026",

series = "Lecture notes in Computer Science",

publisher = "Springer Nature",

pages = "74--85",

editor = "Gabriela Ochoa",

booktitle = "Evolutionary Computation in Combinatorial Optimization",

address = "Switzerland",

}

Analysis of Solution Quality of a Multiobjective Optimization-based Evolutionary Algorithm for Knapsack Problem. / He, Jun; Wang, Yong; Zhou, Yuren.
Evolutionary Computation in Combinatorial Optimization. gol. / Gabriela Ochoa. Cyfrol 9026 Springer Nature, 2015. t. 74-85 (Lecture notes in Computer Science; Cyfrol 9026).

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion Cynhadledd › Trafodion Cynhadledd (Nid-Cyfnodolyn fathau)

TY - GEN

T1 - Analysis of Solution Quality of a Multiobjective Optimization-based Evolutionary Algorithm for Knapsack Problem

AU - He, Jun

AU - Wang, Yong

AU - Zhou, Yuren

PY - 2015/3/15

Y1 - 2015/3/15

N2 - Multi-objective optimisation is regarded as one of the most promising ways for dealing with constrained optimisation problems in evolutionary optimisation. This paper presents a theoretical investigation of a multi-objective optimisation evolutionary algorithm for solving the 0-1 knapsack problem. Two initialisation methods are considered in the algorithm: local search initialisation andgreedy search initialisation. Then the solution quality of the algorithm is analysed in terms of the approximation ratio.

AB - Multi-objective optimisation is regarded as one of the most promising ways for dealing with constrained optimisation problems in evolutionary optimisation. This paper presents a theoretical investigation of a multi-objective optimisation evolutionary algorithm for solving the 0-1 knapsack problem. Two initialisation methods are considered in the algorithm: local search initialisation andgreedy search initialisation. Then the solution quality of the algorithm is analysed in terms of the approximation ratio.

UR - http://hdl.handle.net/2160/30471

U2 - 10.1007/978-3-319-16468-7_7

DO - 10.1007/978-3-319-16468-7_7

M3 - Conference Proceeding (Non-Journal item)

SN - 978-3-319-16467-0

SN - 3319164678

VL - 9026

T3 - Lecture notes in Computer Science

SP - 74

EP - 85

BT - Evolutionary Computation in Combinatorial Optimization

A2 - Ochoa, Gabriela

PB - Springer Nature

ER -

Analysis of Solution Quality of a Multiobjective Optimization-based Evolutionary Algorithm for Knapsack Problem

Crynodeb

Cyfres gyhoeddiadau

Mynediad at Ddogfen

Cysylltiad parhaol

Ffeiliau eraill a chysylltiadau

Ôl bys

Prosiectau

Evolutionary Approximation Algorithms for Optimization: Algorithm design and Complexity Analysis

Dyfynnu hyn