Using anti-pheromone to identify core objects for multidimensional knapsack problems

A two-step ants based approach

Nicolás Rojas, Elizabeth Montero, María Cristina Riffy

Resultado de la investigación: Conference contribution

1 Cita (Scopus)

Resumen

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.

Idioma originalEnglish
Título de la publicación alojadaGECCO 2015 - Companion Publication of the 2015 Genetic and Evolutionary Computation Conference
EditoresSara Silva
EditorialAssociation for Computing Machinery, Inc
Páginas1469-1470
Número de páginas2
ISBN (versión digital)9781450334884
DOI
EstadoPublished - 11 jul 2015
Evento17th Genetic and Evolutionary Computation Conference, GECCO 2015 - Madrid, Spain
Duración: 11 jul 201515 jul 2015

Conference

Conference17th Genetic and Evolutionary Computation Conference, GECCO 2015
PaísSpain
CiudadMadrid
Período11/07/1515/07/15

Huella dactilar

Multidimensional Knapsack Problem
Pheromone
Ant Algorithm
Continue
Optimal Solution
Object

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Artificial Intelligence

Citar esto

Rojas, N., Montero, E., & Riffy, M. C. (2015). Using anti-pheromone to identify core objects for multidimensional knapsack problems: A two-step ants based approach. En S. Silva (Ed.), GECCO 2015 - Companion Publication of the 2015 Genetic and Evolutionary Computation Conference (pp. 1469-1470). Association for Computing Machinery, Inc. https://doi.org/10.1145/2739482.2764713
Rojas, Nicolás ; Montero, Elizabeth ; Riffy, María Cristina. / Using anti-pheromone to identify core objects for multidimensional knapsack problems : A two-step ants based approach. GECCO 2015 - Companion Publication of the 2015 Genetic and Evolutionary Computation Conference. editor / Sara Silva. Association for Computing Machinery, Inc, 2015. pp. 1469-1470
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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.",
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Rojas, N, Montero, E & Riffy, MC 2015, Using anti-pheromone to identify core objects for multidimensional knapsack problems: A two-step ants based approach. En S Silva (ed.), GECCO 2015 - Companion Publication of the 2015 Genetic and Evolutionary Computation Conference. Association for Computing Machinery, Inc, pp. 1469-1470, 17th Genetic and Evolutionary Computation Conference, GECCO 2015, Madrid, Spain, 11/07/15. https://doi.org/10.1145/2739482.2764713

Using anti-pheromone to identify core objects for multidimensional knapsack problems : A two-step ants based approach. / Rojas, Nicolás; Montero, Elizabeth; Riffy, María Cristina.

GECCO 2015 - Companion Publication of the 2015 Genetic and Evolutionary Computation Conference. ed. / Sara Silva. Association for Computing Machinery, Inc, 2015. p. 1469-1470.

Resultado de la investigación: Conference contribution

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Rojas N, Montero E, Riffy MC. Using anti-pheromone to identify core objects for multidimensional knapsack problems: A two-step ants based approach. En Silva S, editor, GECCO 2015 - Companion Publication of the 2015 Genetic and Evolutionary Computation Conference. Association for Computing Machinery, Inc. 2015. p. 1469-1470 https://doi.org/10.1145/2739482.2764713