Multiobjective evolutionary algorithms for operational planning problems in open-pit mining

Rafael F. Alexandre; Felipe Campelo; João A. Vasconcelos

doi:10.1145/3067695.3076004

Multiobjective evolutionary algorithms for operational planning problems in open-pit mining

Rafael F. Alexandre
, Felipe Campelo
, João A. Vasconcelos

College of Engineering and Physical Sciences

Research output: Chapter in Book/Published conference output › Conference publication

Abstract

This paper addresses the problem of planning and allocation of trucks in open-pit mines in terms of three conflicting objectives, and adapts three algorithms for its solution: NSGA-II, SPEA2, and a variant of the Pareto Iterated Local Search using Reduced Variable Neighborhood Search as its local exploration mechanism. Results on four different mining scenarios are also reported and compared.

Original language	English
Title of host publication	Proceedings of the Genetic and Evolutionary Computation Conference - GECCO '17
Publisher	ACM
Pages	259-261
Number of pages	2
ISBN (Print)	9781450349390
DOIs	https://doi.org/10.1145/3067695.3076004
Publication status	Published - 15 Jul 2017

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10.1145/3067695.3076004

Cite this

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title = "Multiobjective evolutionary algorithms for operational planning problems in open-pit mining",

abstract = "This paper addresses the problem of planning and allocation of trucks in open-pit mines in terms of three conflicting objectives, and adapts three algorithms for its solution: NSGA-II, SPEA2, and a variant of the Pareto Iterated Local Search using Reduced Variable Neighborhood Search as its local exploration mechanism. Results on four different mining scenarios are also reported and compared.",

author = "Alexandre, \{Rafael F.\} and Felipe Campelo and Vasconcelos, \{Jo{\~a}o A.\}",

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AU - Vasconcelos, João A.

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N2 - This paper addresses the problem of planning and allocation of trucks in open-pit mines in terms of three conflicting objectives, and adapts three algorithms for its solution: NSGA-II, SPEA2, and a variant of the Pareto Iterated Local Search using Reduced Variable Neighborhood Search as its local exploration mechanism. Results on four different mining scenarios are also reported and compared.

AB - This paper addresses the problem of planning and allocation of trucks in open-pit mines in terms of three conflicting objectives, and adapts three algorithms for its solution: NSGA-II, SPEA2, and a variant of the Pareto Iterated Local Search using Reduced Variable Neighborhood Search as its local exploration mechanism. Results on four different mining scenarios are also reported and compared.

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DO - 10.1145/3067695.3076004

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SP - 259

EP - 261

BT - Proceedings of the Genetic and Evolutionary Computation Conference - GECCO '17

PB - ACM

ER -

Multiobjective evolutionary algorithms for operational planning problems in open-pit mining

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Genetic and Evolutionary Computation Conference, GECCO '17

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Multiobjective evolutionary algorithms for operational planning problems in open-pit mining

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Genetic and Evolutionary Computation Conference, GECCO '17

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