### Abstract

The problem of choosing an open-pit mining investment portfolio can be stated as, given a budget, picking among the possible projects the combination that will incur in the best increase for the mine's productivity when applied. Due to interaction between projects even a seemingly cheap and effective project may not be the most appropriate choice as, in the complete portfolio, it may interact badly with other projects. The objective of this paper is to produce an algorithm capable of finding an adequate solution to this kind of problem in a viable time frame. The proposed heuristic modifies an initial solution through a series of permutation operations with the objective of finding a better solution. Using data and projects from a real Brazilian mine, the algorithm is compared with the current adopted solutions. The algorithm is also used to solve problems of similar classes and its complexity order is estimated. For a collection of 15 projects applied to a medium port mining station, the algorithm is able to find the optimal solution with 93 evaluations of the objective function (in a 3-hour time frame) for the studied instance of the problem. The algorithm also indicates a linear complexity regarding to the number of projects.

Original language | English |
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Title of host publication | 2016 IEEE Congress on Evolutionary Computation (CEC) |

Publisher | IEEE |

Pages | 1525-1532 |

Number of pages | 8 |

ISBN (Electronic) | 978-1-5090-0622-9 |

DOIs | |

Publication status | Published - 14 Nov 2016 |

Event | 2016 IEEE Congress on Evolutionary Computation - Vancouver, Canada Duration: 24 Jul 2016 → 29 Jul 2016 |

### Congress

Congress | 2016 IEEE Congress on Evolutionary Computation |
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Abbreviated title | CEC 2016 |

Country | Canada |

City | Vancouver |

Period | 24/07/16 → 29/07/16 |

### Fingerprint

### Bibliographical note

-### Cite this

*2016 IEEE Congress on Evolutionary Computation (CEC)*(pp. 1525-1532). IEEE. https://doi.org/10.1109/CEC.2016.7743970

}

*2016 IEEE Congress on Evolutionary Computation (CEC).*IEEE, pp. 1525-1532, 2016 IEEE Congress on Evolutionary Computation, Vancouver, Canada, 24/07/16. https://doi.org/10.1109/CEC.2016.7743970

**Portfolio selection for open-pit mining assets acquisition.** / Ferreira, Lucas S.; Wanner, Elizabeth Fialho; Lisboa, Adriano C.; Vieira, Douglas A.G.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Portfolio selection for open-pit mining assets acquisition

AU - Ferreira, Lucas S.

AU - Wanner, Elizabeth Fialho

AU - Lisboa, Adriano C.

AU - Vieira, Douglas A.G.

N1 - -

PY - 2016/11/14

Y1 - 2016/11/14

N2 - The problem of choosing an open-pit mining investment portfolio can be stated as, given a budget, picking among the possible projects the combination that will incur in the best increase for the mine's productivity when applied. Due to interaction between projects even a seemingly cheap and effective project may not be the most appropriate choice as, in the complete portfolio, it may interact badly with other projects. The objective of this paper is to produce an algorithm capable of finding an adequate solution to this kind of problem in a viable time frame. The proposed heuristic modifies an initial solution through a series of permutation operations with the objective of finding a better solution. Using data and projects from a real Brazilian mine, the algorithm is compared with the current adopted solutions. The algorithm is also used to solve problems of similar classes and its complexity order is estimated. For a collection of 15 projects applied to a medium port mining station, the algorithm is able to find the optimal solution with 93 evaluations of the objective function (in a 3-hour time frame) for the studied instance of the problem. The algorithm also indicates a linear complexity regarding to the number of projects.

AB - The problem of choosing an open-pit mining investment portfolio can be stated as, given a budget, picking among the possible projects the combination that will incur in the best increase for the mine's productivity when applied. Due to interaction between projects even a seemingly cheap and effective project may not be the most appropriate choice as, in the complete portfolio, it may interact badly with other projects. The objective of this paper is to produce an algorithm capable of finding an adequate solution to this kind of problem in a viable time frame. The proposed heuristic modifies an initial solution through a series of permutation operations with the objective of finding a better solution. Using data and projects from a real Brazilian mine, the algorithm is compared with the current adopted solutions. The algorithm is also used to solve problems of similar classes and its complexity order is estimated. For a collection of 15 projects applied to a medium port mining station, the algorithm is able to find the optimal solution with 93 evaluations of the objective function (in a 3-hour time frame) for the studied instance of the problem. The algorithm also indicates a linear complexity regarding to the number of projects.

UR - http://ieeexplore.ieee.org/document/7743970/

UR - http://www.scopus.com/inward/record.url?scp=85008255157&partnerID=8YFLogxK

U2 - 10.1109/CEC.2016.7743970

DO - 10.1109/CEC.2016.7743970

M3 - Conference contribution

AN - SCOPUS:85008255157

SP - 1525

EP - 1532

BT - 2016 IEEE Congress on Evolutionary Computation (CEC)

PB - IEEE

ER -