Mine fleet cost evaluation - Dijkstra's optimized path

Abstract

The transport distance in a mining operation strongly influences a mine operation revenue and its operational cycle because it is a fundamental part of the total mining costs. Generally, the transport route is determined based on an engineer's practical knowledge, which does not consider any mechanism to optimize the possible routes to be taken. In an attempt to establish a methodology for calculating the path that results in minimum costs to transport the mined block to its destination, the Dijkstra methodology is applied to a tree graph analysis, where the mining blocks are analysed as nodes of the tree. The transport cost is reflected as the arc of the graphs, which can use the Euclidean distance or the transport time for the calculation of the minimum path. The result obtained from the Dijkstra algorithm provided a non-operational route; to overcome this problem, an adjustment was performed through non-parametric equations. In this manner, it was possible to determine the transport costs for each block of the model. The paths based on Euclidean distance and transport time showed a tendency to increase for deeper mining regions. Identifying areas of largest growth and correctly quantifying their values increase the efficiency of mining planning.

Surface Optimal Path Planning Using an Extended Dijkstra Algorithm

“…When the robot tracks along with the traditional Dijkstra algorithm optimal path, it cannot travel higher or lower than the curved surface and must travel against the curved surface (Refer to the detailed diagram in Fig. 2 (b), l ts (6,11) is the Euclidean space distance between node 6 and node 11, which is higher than the equivalent triangle blocks s (6,7,10) and s (7,10,11) , not on these two triangles). Accordingly, the actual path length with the traditional Dijkstra algorithm optimal path will be much larger than the theory or simulation path length.…”

“…Felipe Ribeiro Souza et al applied the Dijkstra's method to tree diagram analysis, using mining blocks as nodes of the tree for analysis, and used to calculate the lowest cost route to transport mining blocks to their destination (2019) [7]. The transportation cost was reflected in the arc of the graph, and it could use Euclidean distance or transportation time to calculate the minimum path.…”

Discrete Simulations in Analyzing the Effectiveness of Raw Materials Transportation during Extraction of Low-Quality Deposits

“…Technological systems in mining industry are optimized by implementing various methods based on operations research [8]. The Dijkstra algorithm for defining transportation routes in a mine was used in [9] to demonstrate the influence of selecting roads having particular parameters, e.g., inclination, on the transport cycle times. A waiting line system consisting of machines operated in a technological system of a mine was analyzed by Krause et al [10], who suggested the application of a model based on a waiting line analysis (Finite Source Model) in designing the size of the machinery fleet in a mine.…”