Using anti-pheromone to identify core objects for multidimensional knapsack problems: A two-step ants based approach

Nicolás Rojas, Elizabeth Montero, María Cristina Riffy

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

1 Citation (Scopus)

Abstract

This paper proposes a two-step ants algorithm for the Multidimensional Knapsack Problem. In the first step, the algorithm uses an Anti-pheromone to detect which objects are less suitable to be part of a near-optimal solution solving the opposite problem. From this information, in the second step an ant-based algorithm continues searching for better solutions trying to solve the real problem.

Original languageEnglish
Title of host publicationGECCO 2015 - Companion Publication of the 2015 Genetic and Evolutionary Computation Conference
EditorsSara Silva
PublisherAssociation for Computing Machinery, Inc
Pages1469-1470
Number of pages2
ISBN (Electronic)9781450334884
DOIs
Publication statusPublished - 11 Jul 2015
Event17th Genetic and Evolutionary Computation Conference, GECCO 2015 - Madrid, Spain
Duration: 11 Jul 201515 Jul 2015

Conference

Conference17th Genetic and Evolutionary Computation Conference, GECCO 2015
Country/TerritorySpain
CityMadrid
Period11/07/1515/07/15

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Artificial Intelligence

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