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This paper focusses mainly on improving superheated water extraction conditions using the simulation optimization approach known as "steepest ascent".
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The objective function (total fire-risk) of the solution found using the simulation-optimization model was significantly lower than the objective function of a solution found using a greedy heuristic a spatially blind approach, by which the highest risk stands were iteratively removed until the allowable limit on fuel-breaks was reached.
Using the simulation-through-optimization approach, the efficiencies inherent in heuristic optimization techniques can be used to simulate the effects of natural disturbance processes and management policies.
Fig. 9 Convergence for the best solution obtained using the proposed simulation-optimization method.
LID implementation strategies were optimized using the optimization-simulation model for five different implementation scenarios for each of the three storm events with the objectives of minimizing peak flow in the stormsewers, reducing total runoff, and minimizing cost.
The obtained numerical results indicate that using this simulation-optimization model provides accurate results at a less number of iterations when compared with the model employing the classical one-level ICA.
As a real case study, the optimum operating setting of a paint shop production line of automotive company is determined using hybrid simulation optimization approach.
The methodology uses a simulation optimization technique called Reinforcement Learning (RL) and was tested on a stochastic lot-scheduling problem (SELSP) having a state action space of size 1.8 × 107.
To minimize potential noise emissions already in an early design phase of new products (avoiding the costly production of prototypes), it is necessary to use simulation, optimization and control techniques based on mathematical models of the vehicle.
Unfortunately, when metaheuristics are used, simulation optimization can be very much time consuming, since each solution has to be compared on a number of different environments.
It is offered to use the optimization-simulation approach for these purposes.
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