Using parallel computing in modeling and optimization of mineral reserves extraction systems
Annotation This article describes algorithm for solving ultimate pit limit problem (UPIT), or a maximum weight closure problem. There are several method for solving this problem. We provide new approach, for solving ultimate pit limit problem using precedence model. Block model of open pit can be easily represented as an oriented graph. Then to solve ultimate pit limit problem it is required to find such a sub graph in a graph whose sum of weights will be maximal. One of the possible solutions of this problem is using genetic algorithms. We use a parallel genetic algorithm for accelerating of computational process. In this version of algorithm fitness function of each individual calculating in different thread. It allows reducing running time of algorithm. Details of implementation parallel genetic algorithm for searching open pit limits are provided. Comparison with other methods and results of computational experiments provided.
Keywords: open pit limits, genetics algorithms, high-performance computing