Abstract
Truck allocation problems are considered as one of the most substantial factors in the achievement of planned produc- tion capacity in the mining industry. Traditional truck allocation techniques (e.g. mathematical programming, queueing theories) have undergone different levels of simplifications in formulating actual haulage operations under heterogene- ous circumstances. In this study, the truck allocation problem is analysed through the development of the simulation- based optimization (SBO) method for the optimization of truck assignment considering uncertainties during fleet op- eration. This method provides an integrated structure by the simultaneous combination of optimization and stochastic discrete-event simulation. The objective function is to minimize the total number of trucks for haulage operation with discrete-event simulation employed to model the constraints. As a case study, the fleet operation of the Sungun copper mine is investigated to accomplish an optimal truck allocation for various working benches in the mine site. Operation details are evaluated through different indicators such as utilization, waiting times, and the amount of transported ma- terials for each working bench. Finally, the operation bottlenecks are recognized for each situation.
Highlights
A shovel-truck system is considered as one of the most prevalent raw material transportation systems in open-pit mines
As a matter of fact, an imprecise determination of the required number of trucks leads to major challenges during a haulage operation including shovel idle times, truck waiting times and queues at shovels
The optimal truck allocation is derived by modelling and formulation of stochastic procedures during a haulage operation comprising waiting times of trucks, shovel idle times, stochastic times for truck load, haul, dump and return processes
Summary
A shovel-truck system is considered as one of the most prevalent raw material transportation systems in open-pit mines. The DES overcomes the limitations and deficiencies of the previous techniques such as analytical methods, mathematical programming, and queueing theories. In other words, it formulates the actual haulage operation with a lower level of simplification, a high level of operational constraints and stochastic phenomena. This study is aimed to develop a simulation-based optimization method for the allocation of trucks to a loading system. In this approach, the optimal truck allocation is derived by modelling and formulation of stochastic procedures during a haulage operation comprising waiting times of trucks, shovel idle times, stochastic times for truck load, haul, dump and return processes. The proposed simulation-based optimization method works based on making a systematic linkage between the objective function and DES model in such a way that the DES is consecutively connected to the objective function and evaluates it until the optimum solutions are found
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