A cooperative opposite-inspired learning strategy for ant-based algorithms

Nicolás Rojas-Morales, María Cristina Riff, Carlos A. Coello Coello, Elizabeth Montero

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

2 Citations (Scopus)


In recent years, there has been an increasing interest in Opposite Learning strategies. In this work, we propose COISA, a Cooperative Opposite-Inspired Strategy for Ants. Inspired on the concept of anti-pheromone, in this approach, sub-colonies of ants perform different search processes to construct an initial pheromone matrix. We aim to produce a repel effect to (temporarily) avoid components that were related to an undesirable characteristic. To assess the effectiveness of COISA, we selected Ant Knapsack, a well-known ant-based algorithm that efficiently solves the Multidimensional Knapsack Problem. Results in benchmark instances show that the performance of Ant Knapsack is improved considering the opposite information, so that it can reach better solutions than before.

Original languageEnglish
Title of host publicationSwarm Intelligence - 11th International Conference, ANTS 2018, Proceedings
EditorsChristian Blum, Andreagiovanni Reina, Marco Dorigo, Mauro Birattari, Anders L. Christensen, Vito Trianni
PublisherSpringer Verlag
Number of pages8
ISBN (Print)9783030005320
Publication statusPublished - 1 Jan 2018
Event11th International Conference on Swarm Intelligence, ANTS 2018 - Rome, Italy
Duration: 29 Oct 201831 Oct 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11172 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference11th International Conference on Swarm Intelligence, ANTS 2018

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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