A Comparison of Algorithms for Solving Multicomponent Optimization Problems

被引：2

作者：

Vieira, D. K. S. ^{[1
,2
]}

Mendes, M. H. S. ^{[3
]}

机构：

[1] Univ Fed Minas Gerais, Ciencia Comp, Belo Horizonte, MG, Brazil

[2] Univ Fed Minas Gerais, Lao Nano Comp & Nanotecnol Computac NanoComp, Belo Horizonte, MG, Brazil

[3] Univ Fed Vicosa, Florestal, MG, Brazil

来源：

IEEE LATIN AMERICA TRANSACTIONS | 2017年 / 15卷 / 08期

关键词：

Travelling Thief Problem; Genetic Algorithm; Optimization; Combinatorial Problem;

D O I：

10.1109/TLA.2017.7994795

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Real-world problems are often composed of multiple interdependent components. In this case, benchmark problems that do not represent that interdependency are not a good choice to assess algorithm performance. In recently literature, a benchmark problem called Travelling Thief Problem (TTP) was proposed to better represent real-world multicomponent problems. TTP is a combination of two well-known problems: 0-1 Knapsack Problem and the Travelling Salesman Problem. This paper presents a comparison among three optimization approaches for solving TTP. The comparisons are performed on 60 representative small TTP instances available in the literature.

引用

页码：1474 / 1479

页数：6

共 8 条

[1] Chained Lin-Kernighan for large traveling salesman problems [J].

Applegate, D ;

Cook, W ;

Rohe, A .

INFORMS JOURNAL ON COMPUTING, 2003, 15 (01) :82-92

[2] Socially Inspired Algorithms for the Traveling Thief Problem [J].

Bonyadi, Mohammad Reza ;

Michalewicz, Zbigniew ;

Przybylek, Michal Roman ;

Wierzbicki, Adam .

GECCO'14: PROCEEDINGS OF THE 2014 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, 2014, :421-428

[3]

Bonyadi MR, 2013, 2013 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), P1037

[4] Approximate Approaches to the Traveling Thief Problem [J].

Faulkner, Hayden ;

Polyakovskiy, Sergey ;

Schultz, Tom ;

Wagner, Markus .

GECCO'15: PROCEEDINGS OF THE 2015 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, 2015, :385-392

[5] Improving efficiency of heuristics for the large scale traveling thief problem [J].

Mei, Yi ;

Li, Xiaodong ;

Yao, Xin .

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2014, 8886 :631-643

[6]

Oliveira M. R., 2015, S BRAS PESQ OP SER S

[7] A Comprehensive Benchmark Set and Heuristics for the Traveling Thief Problem [J].

Polyakovskiy, Sergey ;

Bonyadi, Mohammad Reza ;

Wagner, Markus ;

Michalewicz, Zbigniew ;

Neumann, Frank .

GECCO'14: PROCEEDINGS OF THE 2014 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, 2014, :477-484

[8]

Vieira D.K.S., 2017, LECT NOTES COMPUTER, V10197

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