Combined simulation-optimization models have been widely used to address the management of water resources issues. This … paper presents a simulation-optimization model for conjunctive use of surface water and groundwater at a basin-wide scale … basin and irrigation system level. The conjunctive use model that coupled numerical simulation with nonlinear optimization …

regulation. This paper focuses on the simulation-optimization for conjunctive use of surface water and groundwater on a basin … the simulation-optimization model is to minimize shortages in meeting irrigation demands for three irrigation systems … surface water and groundwater interaction while a genetic algorithm is developed as the optimization model. The main goal of …

A model-driven design and optimization methodology for sizing the components of refrigeration cassettes for light … coefficient of performance (COP) showed maximum deviations of±10%. A genetic optimization algorithm was used to design the … cost. The optimization led to two improved cassette designs, which were assembled and tested. One of the optimized …

simulate the energy performance of the entire refrigeration system. The system simulation model was validated against … consumption, cooling capacity and runtime ratio deviated from the experimental data within an error band of ±10%. An optimization … algorithm was built upon the simulation model to size the condenser and evaporator heat transfer areas, and also the cabinet …

addressed. Thus, we suggest using simulation optimization. In our paper, we describe a widely adaptable simulation model for …

simulation that the d value suggested by Johansen (2001) outperforms Hill's suggestion and that the performance often can be …

to a sea port, while in the second one they use dry ports. The systems are evaluated by using discrete-event simulation …

The paper deals with the problem of timed state space generation and exploration in the frame of simulation–optimization … be suitable for the simulation–optimization approach. … of timed state space generation and timed simulation are addressed. It is shown that the established simulation …

weight matrix, the costliest data structure for simulation of Hopfield neural network algorithm for large-scale optimization … optimization problem, which facilitates construction and reconstruction of the weights on demand during a simulation, is exposed …A simulation methodology, which trades space complexity with time complexity, to create the Hopfield neural network …

simulation. DOE may have two goals: sensitivity analysis including factor screening and optimization. This contribution starts … simulation models. This contribution discusses the different types of DOE for these three domains, but focusses on random … Bifurcation. Then it discusses Kriging including Latin Hyper cube Sampling and sequential designs. It ends with optimization …