Solving Open-Pit Long-Term Production Planning problems with constraint programming a performance evaluation

Ricardo Soto, Broderick Crawford, Boris Almonacid, Franklin Johnson, Eduardo Olguín

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Open pit mining problems aims at correctly identifying the set of blocks to be mined in order to maximize the net present value of the extracted ore. Different constraints can be involved and may vary the difficulty of the problem. In particular, the Open-Pit Long-Term Production Planning Problem is one of the variants that better models the real mining operation. It considers, among others, limited processing plant and mining capacity as well as slope and grade blending constraints. During the last thirty years, different techniques have been proposed to solve the multiple variants of the open pit mining problem; however, the resolution via constraint programming has not been reported yet. In this paper, we present a performance evaluation of seven constraint programming solvers for the open pit mining long-term scheduling problem. We illustrate interesting and comparative results on a set of varied open pit mining instances.

Original languageEnglish
Title of host publicationICSOFT-EA 2014 - Proceedings of the 9th International Conference on Software Engineering and Applications
EditorsAndreas Holzinger, Therese Libourel, Leszek Maciaszek, Leszek Maciaszek, Stephen Mellor
PublisherSciTePress
Pages70-77
Number of pages8
ISBN (Electronic)9789897580369
DOIs
StatePublished - 2014
Event9th International Conference on Software Engineering and Applications, ICSOFT-EA 2014 - Vienna, Austria
Duration: 29 Aug 201431 Aug 2014

Publication series

NameICSOFT-EA 2014 - Proceedings of the 9th International Conference on Software Engineering and Applications

Conference

Conference9th International Conference on Software Engineering and Applications, ICSOFT-EA 2014
Country/TerritoryAustria
CityVienna
Period29/08/1431/08/14

Keywords

  • Decision support systems
  • Intelligent problem solving
  • Optimization

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