simulation optimization is a scientific tool that is widely used to design and optimize comminution circuits in mineral processing plants. In this research, first of all, in order to  determine the suitable d80 for cicuit hydrocyclone underflow, the requiremed parameters of simulator (residence time distribution, breakage function, selection function and Plitt’s model calibration) were determin...

“Stochastic simulation optimization” (often shortened as simulation optimization) refers to stochastic optimization using simulation. Specifically, the underlying problem is stochastic and the goal is to find the values of controllable parameters (decision variables) to optimize some performance measures of interest, which are evaluated via stochastic simulation, such as discrete-event simulati...

A stochastic optimization approach is presented for the remediation design of a contaminated aquifer with limited hydrogeologic information. Stochastic simulation using the Monte Carlo technique, produces a series of equally probable realisations of the spatially varying random hydraulic conductivity field. The stochastic flow and transport simulation model is coupled, using the response matrix...

When using optimization techniques based on mathematical models, we often need to make important simplifications. The solution thus provided, even if proven to be theoretically one of the best, might not be so good in practice. Simulation can be used to evaluate the actual performance of the solution. We propose here a coupling between optimization and simulation that tries to improve the solut...

In this paper, we present a new approach for automatic design of electrodes. The investigated method consists in identifying an optimal shape from an optimal equipotential resulting from a system of point charges. The electric field and potential are computed using the point charge simulation method. Niching genetic algorithms and constrained optimization techniques are applied to the electrod...

This paper, considers Network Failure Manufacturing System (NFPMS) and production control policy of unreliable multi-machines, multi-products with perishable items. The production control policy is based on the Hedging Point Policy (HPP). The important point in the simulation of this system is assumed that the customers who receive perishable item are placed in priority queue of the customers w...

Metaheuristics have been established as one of the most practical approach to simulation optimization. However, these methods are generally designed for combinatorial optimization, and their implementations do not always adequately account for the presence of simulation noise. Research in simulation optimization, on the other hand, has focused on convergent algorithms, giving rise to the impres...

A new structure learning approach for Bayesian networks (BNs) based on asexual reproduction optimization (ARO) is proposed in this letter. ARO can be essentially considered as an evolutionary based algorithm that mathematically models the budding mechanism of asexual reproduction. In ARO, a parent produces a bud through a reproduction operator; thereafter the parent and its bud compete to survi...