Population-Based Guided Local Search: Some preliminary experimental results

Nasser Tairan; Qingfu Zhang

doi:10.1109/CEC.2010.5586062

Population-Based Guided Local Search: Some preliminary experimental results

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

7 Citations (Scopus)

Abstract

Based on the Proximate Optimality Principle in metaheuristics, a Population Based Guided Local Search (P-GLS) framework for dealing with difficult combinatorial optimization problems is suggested in this paper. In P-GLS, several guided local search (GLS) procedures (agents) run in a parallel way. These agents exchange information during some time points in the search. The information exchanged is the best solutions found so far by these agents. Each agent use such information to adjust its search behavior for moving to a more promising search region. Some preliminary experiments have been conducted on the traveling salesman problem to study the effectiveness of P-GLS. © 2010 IEEE.

Original language	English
Title of host publication	2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010
DOIs	https://doi.org/10.1109/CEC.2010.5586062
Publication status	Published - 2010
Externally published	Yes
Event	2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010 - Barcelona, Spain Duration: 18 Jul 2010 → 23 Jul 2010

Conference

Conference	2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010
Place	Spain
City	Barcelona
Period	18/07/10 → 23/07/10

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@inproceedings{943ed1b82c4341459d6cc59a69fc7749,

title = "Population-Based Guided Local Search: Some preliminary experimental results",

abstract = "Based on the Proximate Optimality Principle in metaheuristics, a Population Based Guided Local Search (P-GLS) framework for dealing with difficult combinatorial optimization problems is suggested in this paper. In P-GLS, several guided local search (GLS) procedures (agents) run in a parallel way. These agents exchange information during some time points in the search. The information exchanged is the best solutions found so far by these agents. Each agent use such information to adjust its search behavior for moving to a more promising search region. Some preliminary experiments have been conducted on the traveling salesman problem to study the effectiveness of P-GLS. {\textcopyright} 2010 IEEE.",

author = "Nasser Tairan and Qingfu Zhang",

year = "2010",

doi = "10.1109/CEC.2010.5586062",

language = "English",

isbn = "9781424469109",

booktitle = "2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010",

note = "2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010 ; Conference date: 18-07-2010 Through 23-07-2010",

}

Tairan, N & Zhang, Q 2010, Population-Based Guided Local Search: Some preliminary experimental results. in 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010., 5586062, 2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010, Barcelona, Spain, 18/07/10. https://doi.org/10.1109/CEC.2010.5586062

Population-Based Guided Local Search: Some preliminary experimental results. / Tairan, Nasser; Zhang, Qingfu.
2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010. 2010. 5586062.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Population-Based Guided Local Search

T2 - 2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010

AU - Tairan, Nasser

AU - Zhang, Qingfu

PY - 2010

Y1 - 2010

N2 - Based on the Proximate Optimality Principle in metaheuristics, a Population Based Guided Local Search (P-GLS) framework for dealing with difficult combinatorial optimization problems is suggested in this paper. In P-GLS, several guided local search (GLS) procedures (agents) run in a parallel way. These agents exchange information during some time points in the search. The information exchanged is the best solutions found so far by these agents. Each agent use such information to adjust its search behavior for moving to a more promising search region. Some preliminary experiments have been conducted on the traveling salesman problem to study the effectiveness of P-GLS. © 2010 IEEE.

AB - Based on the Proximate Optimality Principle in metaheuristics, a Population Based Guided Local Search (P-GLS) framework for dealing with difficult combinatorial optimization problems is suggested in this paper. In P-GLS, several guided local search (GLS) procedures (agents) run in a parallel way. These agents exchange information during some time points in the search. The information exchanged is the best solutions found so far by these agents. Each agent use such information to adjust its search behavior for moving to a more promising search region. Some preliminary experiments have been conducted on the traveling salesman problem to study the effectiveness of P-GLS. © 2010 IEEE.

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DO - 10.1109/CEC.2010.5586062

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9781424469109

BT - 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010

Y2 - 18 July 2010 through 23 July 2010

ER -

Population-Based Guided Local Search: Some preliminary experimental results

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