Comparative analysis of three metaheuristics for short-term open pit block sequencing

Amin Mousavi, Erhan Kozan () and Shi Qiang Liu
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Amin Mousavi: Queensland University of Technology
Erhan Kozan: Queensland University of Technology
Shi Qiang Liu: Queensland University of Technology

Journal of Heuristics, 2016, vol. 22, issue 3, No 3, 329 pages

Abstract: Abstract This paper presents the application of simulated annealing (SA), Tabu search (TS) and hybrid TS–SA to solve a real-world mining optimisation problem called open pit block sequencing (OPBS). The OPBS seeks the optimum extraction sequences under a variety of geological and technical constraints over short-term horizons. As industry-scale OPBS instances are intractable for standard mixed integer programming (MIP) solvers, SA, TS and hybrid TS–SA are developed to solve the OPBS problem. MIP exact solution is also combined with the proposed metaheuristics to polish solutions in feasible neighbourhood moves. Extensive sensitivity analysis is conducted to analyse the characteristics and determine the optimum sets of values of the proposed metaheuristics algorithms’ parameters. Computational experiments show that the proposed algorithms are satisfactory for solving the OPBS problem. Additionally, this comparative study shows that the hybrid TS–SA is superior to SA or TS in solving the OPBS problem in several aspects.

Keywords: Open pit mining; Short-term block sequencing; Mixed integer programming; Simulated annealing; Tabu search; Hybrid metaheuristic (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s10732-016-9311-z

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