Towards Solving Large-Scale Precedence Constrained Production Scheduling Problems in Mining

Kenny, A, Li, X, Ernst, A and Thiruvady, D 2017, 'Towards Solving Large-Scale Precedence Constrained Production Scheduling Problems in Mining', in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2017), Berlin, Germany, 15 - 19 July 2017, pp. 1137-1144.


Document type: Conference Paper
Collection: Conference Papers

Title Towards Solving Large-Scale Precedence Constrained Production Scheduling Problems in Mining
Author(s) Kenny, A
Li, X
Ernst, A
Thiruvady, D
Year 2017
Conference name GECCO 2017
Conference location Berlin, Germany
Conference dates 15 - 19 July 2017
Proceedings title Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2017)
Publisher Association for Computing Machinery
Place of publication United States
Start page 1137
End page 1144
Total pages 8
Abstract Pit planning and long-term production scheduling are important tasks within the mining industry. This is a great opportunity for optimisation techniques, as the scale of a lot of mining operations means that a small percentage increase in efficiency can translate to millions of dollars in profit. The precedence constrained production scheduling problem (PCPSP) combines both of these aspects of mine optimisation and aims to find a solution which tells a mining company what part of the orebody to mine, and at what time during the life of the mine. This paper presents a GRASP-Mixed Integer Programming hybrid metaheuristic algorithm for solving the PCPSP which consists of two parts: a fast, period-by-period, random construction phase and a local improvement heuristic. It is compared to the current published state-of-the-art results on well known benchmark problems from minelib [5] and is shown to give better quality results in four of the six instances, and within 2% of the LP upper bound in the remaining two. The PCPSP is a good candidate for hybrid metaheuristics as the size of the problems make solving them with mathematical solvers alone intractable.
Subjects Optimisation
Neural, Evolutionary and Fuzzy Computation
Keyword(s) Mine planning
mixed integer programming
hybrid methods
DOI - identifier 10.1145/3071178.3071241
Copyright notice © 2017 ACM
ISBN 9781450349208
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