Recent metaheuristics for the Weighted Set Covering problem

Broderick Crawford, Ricardo Soto, Rodrigo Cuesta, Miguel Olivares-Suárez, Franklin Johnson

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The Weighted Set Covering problem is a formal model for many industrial optimization problems. In the Weighted Set Covering Problem the goal is to choose a subset of columns of minimal cost in order to cover every row. Here, we present its resolution with two novel metaheuristics: Firefly Algorithm and Artificial Bee Colony Algorithm. The Firefly Algorithm is inspired by the flashing behaviour of fireflies. The main purpose of flashing is to act as a signal to attract other fireflies. The flashing light can be formulated in such a way that it is associated with the objective function to be optimized. The Artificial Bee Colony Algorithm mimics the food foraging behaviour of honey bee colonies. In its basic version the algorithm performs a kind of neighbourhood search combined with random search. Experimental results show that both are competitive in terms of solution quality with other recent metaheuristic approaches.

Original languageEnglish
Title of host publicationOPT-i 2014 - 1st International Conference on Engineering and Applied Sciences Optimization, Proceedings
EditorsN. D. Lagaros, Matthew G. Karlaftis, M. Papadrakakis
PublisherNational Technical University of Athens
Pages495-509
Number of pages15
ISBN (Electronic)9789609999465
StatePublished - 2014
Event1st International Conference on Engineering and Applied Sciences Optimization, OPT-i 2014 - Kos Island, Greece
Duration: 4 Jun 20146 Jun 2014

Publication series

NameOPT-i 2014 - 1st International Conference on Engineering and Applied Sciences Optimization, Proceedings

Conference

Conference1st International Conference on Engineering and Applied Sciences Optimization, OPT-i 2014
Country/TerritoryGreece
CityKos Island
Period4/06/146/06/14

Keywords

  • Artificial bee colony algorithm
  • Firefly algorithm
  • Metaheuristics
  • Swarm intelligence
  • Weighted set covering problem

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