A cooperative learning approach for the quadratic Knapsack problem

Eduardo Lalla-Ruiz, Eduardo Segredo, Stefan Voß*

*Corresponding author for this work

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

1 Citation (Scopus)
1 Downloads (Pure)

Abstract

The Quadratic Knapsack Problem (QKP) is a well-known optimization problem aimed to maximize a quadratic objective function subject to linear capacity constraints. It has several applications in different fields such as telecommunications, graph theory, logistics, hydrology and data allocation, among others. In this paper, we propose the application of a novel population-based metaheuristic referred to as Multi-leader Migrating Birds Optimization (MMBO), which exploits the concepts of cooperation and communication along the search leading to a collective learning, to solve a wide range of well-known QKP instances.

Original languageEnglish
Title of host publicationLearning and Intelligent Optimization
Subtitle of host publication12th International Conference, LION 12, Revised Selected Papers
EditorsPanos M. Pardalos, Roberto Battiti, Mauro Brunato, Ilias Kotsireas
PublisherSpringer
Pages31-35
Number of pages5
ISBN (Electronic)978-3-030-05348-2
ISBN (Print)978-3-030-05347-5
DOIs
Publication statusPublished - 31 Dec 2018
Event12th International Conference on Learning and Intelligent Optimization, LION 2018 - Elite City Resort, Kalamata, Greece
Duration: 10 Jun 201815 Jun 2018
Conference number: 12
http://www.caopt.com/LION12/

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11353 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th International Conference on Learning and Intelligent Optimization, LION 2018
Abbreviated titleLION 2018
CountryGreece
CityKalamata
Period10/06/1815/06/18
Internet address

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