Artificial intelligence methods and search techniques such as simulated annealing and simultaneous perturbation can be used in simulation optimization of complex stochastic systems. Simultaneous perturbation has also been applied in the area of neural networks. Simulation optimization methods are often used when it is difficult to obtain the closed form of the objective function, but it is poss...

Permanent magnet synchronous generators (PMSG) have a huge potential for direct-drive wind power applications. Therefore, optimal design of these generators is necessary to maximize their efficiency and to reduce their manufacturing cost and total volume. In this paper, an optimal design of a six-phase 3.5 KW direct-drive PMSG to generate electricity for domestic needs is performed. The aim of ...

This paper presents a successful application of simulationbased multi-objective optimization of a complex real-world scheduling problem. Concepts of the implemented simulation-based optimization architecture are described, as well as how different components of the architecture are implemented. Multiple objectives are handled in the optimization process by considering the decision makers’ prefe...

in thermal cracking plants, it is desired to apply an optimal temperature profile along the reactor to minimize the operation cost. in this article a simulator is developed by the use of a mathematical model, which describes the static operation of a naphtha thermal cracking pilot plant. the model is used to predict the steady state profiles of the gas temperature and product yields. using a dy...

Simulation with integrated parameter optimization of a given model structure is a well-established technique today. However, with increasing system complexity and flexibility the number of possible structure variants increases. Therefore the potential benefit of automatic model structure optimization becomes significant. During optimization, the introduced framework supports automatic parameter...

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...

The paper deals with the distributed solution of simulation based nonlinear constrained optimization problems in engineering on a network of workstations. This type of non-linear optimization and control problems in engineering can be generally characterized as non{convex and non-smooth. Additionally, the involved simulation introduces certain numerical "noise\ to the solution process. These ch...

The researchers made significant progress in all of the proposed research areas. The first major task in the proposal involved simulation-based and sampling methods for global optimization. In support of this task, we have discovered two new innovative approaches to simulation-based global optimization; the first involves connections between stochastic approximation and our model reference appr...

The numerical simulation research of the Underwater Unmanned Vehicle (UUV) shell shape is carried out by applying the modern fluid dynamics numerical simulation technology. In the numerical simulation process, while focusing on the characteristics of the UUV shape, this treatise work properly with its computational model, computational domain, computational grid and boundary conditions. Based o...

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...