Simulation-based optimization approach for material dispatching in continuous mining systems

Abstract

This paper examines a problem related to dispatching materials to spreaders in coal (lignite) mines operated under the paradigm of continuously excavated material flow. In the considered particular case, complexity arises from different material types of overburden to be placed on the dump site in pre-defined patterns that guarantee geotechnical safety. These types include wet, semi-wet and dry material, which are accessed on the excavation site according to the geological deposition and the mining plan. Controlling of the dispatch system has to take into account the extraction sequence and geological stratification on the excavation site and the available dump space per material on the dumping site. With eight excavators on the excavation site and seven spreaders on the dump site the problem is already complex, having not stated yet that random breakdowns may make some options temporarily unavailable. To optimize the dispatch system in terms of minimum idle time due to unavailability of dumping space, a new multi-stage simulation-based optimization approach is proposed. This approach consists of running alternatingly a deterministic optimization model and a stochastic simulation model. It combines simulation and algorithms to solve a transportation problem and a job-shop scheduling problem. The proposed approach is tested on a large continuous mine under given different dumping sequences, and results are reported. The merits and limitations of the proposed approach as pinpointed and farsighted operations management are discussed.

Simulation‐Based Multiobjective Optimization of Open‐Pit Mine Haulage System: A Modified‐NBI Method and Meta Modeling Approach

“…e idea of optimization based on simulation is presented to find optimal or near-optimal solutions. Choosing a suitable approach for optimization depends on the characteristics of the problem [28]. In terms of choosing the approach, we classify optimization based on simulation into two types.…”

“…e Meta-model estimated in this study can reduce the deviation in results and current costs in the system. Shishvan et al [28] have presented a new approach for simulation optimization to solve the problems of transportation and job-shop scheduling. Based on the obtained results, the quality of the obtained solutions increases compared to other considered algorithms.…”

The cashier service macroprocess analysis in a supermarket organization: a quality management and simulation case study

“…The search for the improvement of productive systems is also a reality that can be understood from the perspective of Process Simulation [14]. In this sense, simulation represents a tool for analyzing scenarios and assisting organizations in decision-making processes [13]. In addition, Process Simulation is based on the creation of models that faithfully represent the basic and essential aspects of the analyzed reality [22].…”

“…Regarding Routine Management, it is based on the greater autonomy of employees to solve daily problems, providing greater effectiveness and operational efficiency [8,12]. In addition to Process Analysis and Routine Management, Process Simulation can be incorporated in this context as a complementary measure to aid in the effective diagnosis of operations [13]. In view of this, Process Simulation has applicability in the solution of real problems through the anticipation of adverse situations in the system, as well as in the performance evaluation of the system [14].…”

Integrated optimization and simulation models for short-term open-pit mine planning

“…The proposed system increased production by 9.4% in a shift, compared to the previous dispatching system used in the mine of the presented case study (Ozdemir and Kumral, 2019). Shishvan and Benndorf (2019) proposed a new multi-stage simulation-based optimization approach combining deterministic optimization with stochastic simulation in order to solve a transportation and scheduling problem in a continuous coalmining process. Stochastic optimization is also used for modelling and solving optimization problems under uncertainty.…”