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: Contribución a los tipos de informe/libroContribución a la conferencia

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 originalInglés
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
EstadoPublicada - 11 jul 2015
Evento17th Genetic and Evolutionary Computation Conference, GECCO 2015 - Madrid, Espana
Duración: 11 jul 201515 jul 2015

Conferencia

Conferencia17th Genetic and Evolutionary Computation Conference, GECCO 2015
PaísEspana
CiudadMadrid
Período11/07/1515/07/15

Áreas temáticas de ASJC Scopus

  • Software
  • Ciencia computacional teórica
  • Inteligencia artificial

Huella Profundice en los temas de investigación de 'Using anti-pheromone to identify core objects for multidimensional knapsack problems: A two-step ants based approach'. En conjunto forman una huella única.

  • 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