In this paper, we propose a method for supporting decision makers in the domain of supply chain management. Our objective is the global optimization instead of optimizing independent subsystems of the supply chain. The method architecture is based on combination of the simulation and optimization techniques which includes a multi-objectives optimization module and a simulation module. The optim...

this paper presents a new optimization algorithm to design an optimal proportional, integral, derivative (pid) controller in hydro-turbine generator governor for damping output frequency oscillations. in this research, we utilize a stochastic and optimal based pid controller to control frequency-response of the hydro turbine. the proposed algorithm is employed to design an optimal pid controlle...

Simulation optimization is rapidly becoming a mainstream tool for simulation practitioners, as several simulation packages include add-on optimization tools. In this paper we are concentrating on an automated optimization approach that is based on adapting model parameters in order to handle uncertainty that arises from stochastic elements of the process under study. We particularly investigate...

A proposal for particles’ initialization in PSO is presented and discussed, with focus on costly global unconstrained optimization problems. The standard PSO iteration is reformulated such that the trajectories of the particles are studied in an extended space, combining particles’ position and speed. To the aim of exploring effectively and efficiently the optimization search space since the ea...

  The simulation of distillation columns is an essential step in design, optimization, and rating. In this paper, a new procedure has been proposed for the initial estimation of column profiles based on modified Kremser’s group method for simple and/or complex columns. The effect of this initialization algorithm on simulation procedure has been studied through two examples. The results show sig...

There is a strong need for sound statistical analysis of simulation and optimization algorithms. Based on this analysis, improved parameter settings can be determined. This will be referred to as tuning. Model-based investigations are common approaches in simulation and optimization. The sequential parameter optimization toolbox SPOT package for R [5] is a toolbox for tuning and understanding s...

In this study, we explore the impact of noise handling strategies on optimization performance in the context of a real-world production planning problem. Uncertainties intrinsic to the production system are captured using a discrete event simulation (DES) model, and the production plan is optimized using an evolutionary algorithm. The stochastic nature of the fitness values (as returned by the ...

Design, architecture and deployment details of a decision support system engineered to minimize operating costs of compressor stations in a gas network are presented. The system employs standard simulation software for pipelines, combined with well known optimization routine for finding optimal station control profiles in a repetitive way. A list of custom improvements is presented that make th...