Optimization Of Short Term Production Scheduling In Open Pit Mine

A critical part of open-pit mine operation is to arrange the optimal block scheduling for the extraction,which influences mining benefit extensively.The hard problem which is faced in this part,block scheduling in open pit mine problem,is the arrangement keeping in mind the end goal to determine the optimal scheduling of the blocks extraction in light of several technical and physical constraints.This research introduces a comprehensive mathematical model for block scheduling in open pit mine problem which has taken into account technical conditions of real-life mining operations.In this model,the attributes of the blocks,destination assignments,block scheduling,grade control and stockpiles are researched and integrated to satisfy the production targets and to essentially decrease the stockpiling costs.Contrasted with the old models of mine block scheduling,this model is developed according to the block unit(smallest mining unit),while all constraints such as grade,processing,and precedence relationships requirements are fulfilled.The block scheduling in open pit is a NP-hard problem,so standard integer programming solvers can't solve industrial-scale instances for this problem.Therefore,heuristics and meta-heuristics algorithms,including constructive heuristic,simulated annealing,tabu search and local search have created and coded in the MATLAB software.Tabu search and simulated annealing are creatively hybridized to come up with a new hybridized algorithm have the features of both of them.In order to validate the proposed heuristic algorithms,a comparison performed between the outcomes of these algorithms and the outcomes of a standard solver(CPLEX),for small cases and also for many large-scale in real life.The practical experiments have shown that the proposed algorithms are quite agreeable to be adopted for solving large-scale cases.In addition,in light of a real data from the field.A sensitivity analysis and numerical investigation are performed to give quantitative and insightful recommendations for the planners and mining engineers.