A Merge Search Algorithm and its Application to the Constrained Pit Problem in Mining

Kenny, A, Li, X and Ernst, A 2018, 'A Merge Search Algorithm and its Application to the Constrained Pit Problem in Mining', in Hernan Aguirre (ed.) Proceedings of the 2018 Conference on Genetic and Evolutionary Computation Conference (GECCO), Kyoto, Japan, 15 - 19 July 2018, pp. 316-323.


Document type: Conference Paper
Collection: Conference Papers

Title A Merge Search Algorithm and its Application to the Constrained Pit Problem in Mining
Author(s) Kenny, A
Li, X
Ernst, A
Year 2018
Conference name 2018 Conference on Genetic and Evolutionary Computation Conference (GECCO)
Conference location Kyoto, Japan
Conference dates 15 - 19 July 2018
Proceedings title Proceedings of the 2018 Conference on Genetic and Evolutionary Computation Conference (GECCO)
Editor(s) Hernan Aguirre
Publisher ACM New York
Place of publication United States
Start page 316
End page 323
Total pages 8
Abstract Many large-scale combinatorial problems contain too many variables and constraints for conventional mixed-integer programming (MIP) solvers to manage. To make the problems easier for the solvers to handle, various meta-heuristic techniques can be applied to reduce the size of the search space, by removing, or aggregating, variables and constraints. A novel meta-heuristic technique is presented in this paper called merge search, which takes an initial solution and uses the information from a large population of neighbouring solutions to determine promising areas of the search space to focus on. The population is merged to produce a restricted sub-problem, with far fewer variables and constraints, which can then be solved by a MIP solver. Merge search is applied to a complex problem from open-pit mining called the constrained pit (CPIT) problem, and compared to current state-of-the-art results on well known benchmark problems minelib [7] and is shown to give better quality solutions in five of the six instances.
Subjects Operations Research
Optimisation
Neural, Evolutionary and Fuzzy Computation
Keyword(s) Hybrid algorithms
mixed integer programming
mine planning
Copyright notice © 2018 Association for Computing Machinery
ISBN 9781450356183
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