Development of a new methodology for path optimization of underground mine haul roads using evolutionary algorithms

---

Tezin Türü: Doktora

Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Mühendislik Fakültesi, Maden Mühendisliği Bölümü, Türkiye

Tezin Onay Tarihi: 2018

Öğrenci: AHMET GÜNEŞ YARDIMCI

Danışman: CELAL KARPUZ

Özet:

The main haul road serves as an access route for men, equipment, transportation of extracted ore and ventilation air in underground mines. Initial capital investment and operating cost parameters are affected by the haul road path. However, the most common method to design a main haul road is to rely on the provisions of skilled mine design experts. Contrary to the simple underground mine layouts, determination of the optimum path without violating navigability constraints in complex underground networks may exceed the limit of human intelligence. Obviously, a new methodology is required to obtain the shortest mine haul road that satisfy the minimum turning radius and maximum gradient constraints. It is also useful to avoid some structural defect zones (like faults, joints) or any kind of undesired regions. In addition to the path length minimization, rock mass quality should also be optimized for increasing safety and decreasing tunnel support costs. This study aims to provide an algorithmic solution to one of the major design problems in underground mine planning. In the first stage, the shortest path optimization is adapted to this specific mining problem. Conventional methods are investigated and an improved solution mechanism is established using evolutionary algorithms. In the second stage, path length and the rock mass quality covering the haul road are optimized by a multi objective optimization. Developed algorithms are verified on simple benchmark problems. Finally, algorithmic designs are compared to the designs of human experts on actively operating underground mines. Advantages of evolutionary algorithms are shown.