Paper Info
Title
The Impact of a New Formulation When Solving the Set Covering Problem Using the ACO Metaheuristic
Abstract
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.
Year
DOI
Venue
2015
10.1007/978-3-319-18167-7_19
MODELLING, COMPUTATION AND OPTIMIZATION IN INFORMATION SYSTEMS AND MANAGEMENT SCIENCES - MCO 2015 - PT II
Keywords
Field
DocType
Set Covering Problem,Ant Colony Optimization,Metaheuristics
Ant colony optimization algorithms,Set cover problem,Mathematical optimization,Computer science,Scheduling (computing),Portfolio,Production planning,Redundancy (engineering),Discrete optimization problem,Metaheuristic
Conference
Volume
ISSN
Citations 
360
2194-5357
0
PageRank 
References 
Authors
0.34
15
6
Name
Order
Citations
PageRank
Broderick Crawford144673.74
Ricardo Soto219447.59
Wenceslao Palma3685.92
Fernando Paredes423027.21
Franklin Johnson5185.76
Enrique Norero641.43