EPSRC Reference: |
GR/J74367/01 |
Title: |
THE APPLICATION OF GENETIC ALGORITHMS TO OPEN PIT DESIGN AND SCHEDULING |
Principal Investigator: |
Denby, Professor B |
Other Investigators: |
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Researcher Co-Investigators: |
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Project Partners: |
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Department: |
Mineral Resources Engineering |
Organisation: |
University of Nottingham |
Scheme: |
Standard Research (Pre-FEC) |
Starts: |
01 February 1994 |
Ends: |
31 January 1997 |
Value (£): |
99,415
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EPSRC Research Topic Classifications: |
Design of Process systems |
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EPSRC Industrial Sector Classifications: |
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Related Grants: |
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Panel History: |
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Summary on Grant Application Form |
The design and scheduling of open pit operations is a consistent problem encountered by the Mining Industry. Although a variety of optimisation techniques have been developed they do not fully account for the time value of money; optimal pit design must consider the schedule of extraction. We propose to apply genetic algorithms to this problem and automatically optimise both the pit limit design and extraction schedule simultaneously. Genetic algorithms differ from traditional search and optimisation methods in that they use coding of the control parameters and adapt the solutions themselves. The work will proceed in a number of phases which include: the generation of random populations, extension of standard genetic operators to optimise multi-dimensional problems, application of practical constraint functions and the introduction of the scheduling/time element. System testing and validation will also be carried out. The inclusion of a time constraint greatly increases the complexity of the optimisation procedure. The genetic algorithm approach requires that populations of models are considered simultaneously. These analyses are iterated over a number of generations. The processing power and data storage capabilities of modern computers allow the manipulation and processing of this data within a realistic time frame, due to greatly increased computation rates.
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Key Findings |
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Potential use in non-academic contexts |
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Impacts |
Description |
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Summary |
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Date Materialised |
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Sectors submitted by the Researcher |
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Project URL: |
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Further Information: |
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Organisation Website: |
http://www.nottingham.ac.uk |