A nested multiple-objective optimization algorithm for managing production fleets in surface mines

Ali Moradi Afrapoli, Shiv Prakash Upadhyay, Hooman Askari-Nasab

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

The fleet management system (FMS) plays a vital role in truck and shovel open-pit mining operations. The list of expectations from the FMS ranges from data recording to making operational decisions. This article proposes a nested fleet management system (N-FMS) for open-pit mining operations. The primary contribution of the proposed FMS is connecting the operation to the strategic plan by incorporating shovel allocation and plant feed optimization. Another contribution of the proposed N-FMS is that it simultaneously optimizes the utilization of the shovel fleet and truck fleet. The proposed FMS makes decisions using two nested multiple-objective mixed-integer linear goal programming models. Results of the implementation of the developed N-FMS in a metal mining case study show that compared to a locked-in operation, the mine experienced a 14.6% improvement in its required truck fleet capacity to meet the production target.

Original languageEnglish
Pages (from-to)378-391
Number of pages14
JournalEngineering Optimization
Volume56
Issue number3
DOIs
StatePublished - 2024

Bibliographical note

Publisher Copyright:
© 2022 Informa UK Limited, trading as Taylor & Francis Group.

Keywords

  • Fleet management system (FMS)
  • multiple-objective decision making
  • nested fleet management system (N-FMS)
  • open-pit mining

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Optimization
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering
  • Applied Mathematics

Fingerprint

Dive into the research topics of 'A nested multiple-objective optimization algorithm for managing production fleets in surface mines'. Together they form a unique fingerprint.

Cite this