### Resumen

This work presents different opposite learning strategies for Ant Knapsack, an ant based algorithm for the Multidimensional Knapsack Problem. We propose to include a previous opposite learning phase to Ant Knapsack, for discarding regions of the search space. This opposite knowledge is then used by Ant Knapsack for solving the original problem. The objective is to improve the search process of Ant Knapsack maintaining its original design. We present three strategies which differ on how the solutions can be constructed on a opposite way. The results obtained are promising and encourage to use this approach for solving other problems.

Idioma original | English |
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Título de la publicación alojada | 2016 IEEE Congress on Evolutionary Computation, CEC 2016 |

Editorial | Institute of Electrical and Electronics Engineers Inc. |

Páginas | 193-200 |

Número de páginas | 8 |

ISBN (versión digital) | 9781509006229 |

DOI | |

Estado | Published - 14 nov 2016 |

Evento | 2016 IEEE Congress on Evolutionary Computation, CEC 2016 - Vancouver, Canada Duración: 24 jul 2016 → 29 jul 2016 |

### Conference

Conference | 2016 IEEE Congress on Evolutionary Computation, CEC 2016 |
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País | Canada |

Ciudad | Vancouver |

Período | 24/07/16 → 29/07/16 |

### Huella dactilar

### ASJC Scopus subject areas

- Artificial Intelligence
- Modelling and Simulation
- Computer Science Applications
- Control and Optimization

### Citar esto

*2016 IEEE Congress on Evolutionary Computation, CEC 2016*(pp. 193-200). [7743795] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CEC.2016.7743795

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*2016 IEEE Congress on Evolutionary Computation, CEC 2016.*, 7743795, Institute of Electrical and Electronics Engineers Inc., pp. 193-200, 2016 IEEE Congress on Evolutionary Computation, CEC 2016, Vancouver, Canada, 24/07/16. https://doi.org/10.1109/CEC.2016.7743795

**Learning from the opposite : Strategies for Ants that solve multidimensional Knapsack problem.** / Rojas-Morales, Nicolás; Riff, R. María Cristina; Montero, U. Elizabeth.

Resultado de la investigación: Conference contribution

TY - GEN

T1 - Learning from the opposite

T2 - Strategies for Ants that solve multidimensional Knapsack problem

AU - Rojas-Morales, Nicolás

AU - Riff, R. María Cristina

AU - Montero, U. Elizabeth

PY - 2016/11/14

Y1 - 2016/11/14

N2 - This work presents different opposite learning strategies for Ant Knapsack, an ant based algorithm for the Multidimensional Knapsack Problem. We propose to include a previous opposite learning phase to Ant Knapsack, for discarding regions of the search space. This opposite knowledge is then used by Ant Knapsack for solving the original problem. The objective is to improve the search process of Ant Knapsack maintaining its original design. We present three strategies which differ on how the solutions can be constructed on a opposite way. The results obtained are promising and encourage to use this approach for solving other problems.

AB - This work presents different opposite learning strategies for Ant Knapsack, an ant based algorithm for the Multidimensional Knapsack Problem. We propose to include a previous opposite learning phase to Ant Knapsack, for discarding regions of the search space. This opposite knowledge is then used by Ant Knapsack for solving the original problem. The objective is to improve the search process of Ant Knapsack maintaining its original design. We present three strategies which differ on how the solutions can be constructed on a opposite way. The results obtained are promising and encourage to use this approach for solving other problems.

UR - http://www.scopus.com/inward/record.url?scp=85008251740&partnerID=8YFLogxK

U2 - 10.1109/CEC.2016.7743795

DO - 10.1109/CEC.2016.7743795

M3 - Conference contribution

SP - 193

EP - 200

BT - 2016 IEEE Congress on Evolutionary Computation, CEC 2016

PB - Institute of Electrical and Electronics Engineers Inc.

ER -