A stochastic hybrid simulation-optimization approach towards haul fleet sizing in surface mines. Issue 1 (2nd January 2019)

• Record Type: Journal Article
• Authors: Moradi Afrapoli, Ali; Tabesh, Mohammad; Askari-Nasab, Hooman
• Is Part Of: Mining technology. Volume 128:Issue 1(2019)
• Page Start: 9
• Page End: 20
• Publication Date: 2019-01-02
• Subjects: Simulation -- optimization -- haul fleet sizing -- truck dispatching -- surface mining -- fleet management; Mining engineering -- Periodicals; Mineral industries -- Periodicals; 662.05; 622.05
• DOI: 10.1080/25726668.2018.1473314
• Languages: English
• ISSNs: 2572-6668

Abstract

ABSTRACT: Haul fleet size determination is a critical task in any surface mining operation where the material is handled using the truck-and-shovel system. Although the problem of finding the optimum haulage fleet size has been thoroughly studied, there are two important shortcomings: disregarding the effects of downstream processes on the operation and ignoring the fleet management system effects. This paper presents an integrated simulation-optimization framework to address the haul fleet size determination problem surface mines and target the two shortcomings listed above. In the developed framework, the mining operation, the processing plants, and the operational decision tools communicate with each other to find the best size of the haul fleet required to meet the production schedule. Results of the study show that the developed framework is capable of handling the operation with 13% less number of trucks than the required number of trucks suggested by deterministic calculations.