Genetic algorithms for optimization of a mine system under uncertainty
Küçük Resim Yok
Tarih
2004
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Taylor & Francis Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The production planning of a mine system associated with mining, processing and refining stages dictates to determine optimal system parameters such as optimal production rates, location of refining facility and the best reconstruction time of production rates. This paper proposes a combination of the chance constrained programming (CCP) and the genetic algorithms (GA) to find the optimal system parameters simultaneously. In generic form the problem is expressed as the maximization of net present value of future cash flows such that the capacity constraint and predefined specifications are satisfied. The blending requirements expressed in the CCP are transformed into deterministic equivalents. A new form of the problem is solved by the GA. The approach was demonstrated on extraction, processing and refining of four iron ore mines with varying reserves, ore qualities, geological and topographic conditions, four mineral processing units and one re. ning facility. The results showed that the proposed algorithm could be used to determine optimal production rates, the facility location and the best reconstruction time.
Açıklama
Anahtar Kelimeler
genetic algorithms, chance constrained programming, optimal location, production rates, reconstruction time
Kaynak
Production Planning & Control
WoS Q Değeri
Q3
Scopus Q Değeri
Q1
Cilt
15
Sayı
1
