The Impact of a New Formulation When Solving the Set Covering Problem Using the ACO Metaheuristic

被引：2

作者：

Crawford, Broderick ^{[1
,2
,3
]}

Soto, Ricardo ^{[1
,4
,5
]}

Palma, Wenceslao ^{[1
]}

Paredes, Fernando ^{[6
]}

Johnson, Franklin ^{[1
,7
]}

Norero, Enrique ^{[8
]}

机构：

[1] Pontificia Univ Catolica Valparaiso, Valparaiso, Chile

[2] Univ Finis Terrae, Providencia, Chile

[3] Univ San Sebastian, Santiago, Chile

[4] Univ Autonoma Chile, Santiago, Chile

[5] Univ Cent Chile, Santiago, Chile

[6] Univ Diego Portales, Escuela Ingn Ind, Santiago, Chile

[7] Univ Playa Ancha, Dept Computac & Informat, Valparaiso, Chile

[8] Univ Santo Tomas, Fac Ingn, Escuela Ingn, Vina Del Mar, Chile

来源：

MODELLING, COMPUTATION AND OPTIMIZATION IN INFORMATION SYSTEMS AND MANAGEMENT SCIENCES - MCO 2015 - PT II | 2015年 / 360卷

关键词：

Set Covering Problem; Ant Colony Optimization; Metaheuristics; ALGORITHM; OPTIMIZATION; COLONY;

D O I：

10.1007/978-3-319-18167-7_19

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The Set Covering Problem (SCP) is a well-known NP hard discrete optimization problem that has been applied to a wide range of industrial applications, including those involving scheduling, production planning and location problems. The main difficulties when solving the SCP with a metaheuristic approach are the solution infeasibility and set redundancy. In this paper we evaluate a state of the art new formulation of the SCP which eliminates the need to address the infeasibility and set redundancy issues. The experimental results, conducted on a portfolio of SCPs from the Beasley's OR-Library, show the gains obtained when using a new formulation to solve the SCP using the ACO metaheuristic.

引用

页码：209 / 218

页数：10

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