Many military planning problems are difficult to solve using pure mathematical programming techniques. One such problem is scheduling unmanned aerial vehicles (UAVs) in military operations subject to dynamic movement and control constraints. This problem is instead formulated as a dynamic programming problem whose approximate solution is obtained via the Assignment Scheduling Capability for UAV...

An emerging, yet extremely important topic in simulation application and research is simulation optimization. Emphasis in the literature, in professional conferences, and particularly in commercial software packages underscore the importance of simulation optimization. We address this topic in a more general, model optimization venue. In particular we describe the use of a genetic algorithm in ...

Discrete-event simulation and (mixed-integer) linear programming are widely used for supply chain planning. We present a general framework to support the operational decisions for supply chain networks using a combination of an optimization model and discrete-event simulation. The simulation model includes nonlinear and stochastic elements, whereas the optimization model represents a simplified...

Simulation models have proved to be useful for examining the performance of different system configurations and/or alternative operating procedures for complex logistic or manufacturing systems. However, when applying simulation techniques to increase the performance of those systems, several limitations arise due to their inability to evaluate more than a fraction of the immense range of optio...

this study investigated the efficiency of wheat farms in sistan province. the data consisted of 50 samples from crop producers in the sistan region. using the simple sampling method, the data was collected by completing the questionnaires. to evaluate the farm efficiencies, the two approaches of the “data envelopment analysis” and the “optimization model including parameters to control for the ...

model predictive controller is widely used in industrial plants. uncertainty is one of the critical issues in real systems. in this paper, the direct adaptive simplified model predictive control (smpc) is proposed for unknown or time varying plants with uncertainties. by estimating the plant step response in each sample, the controller is designed and the controller coefficients are directly ca...

in this paper, reduced order proper orthogonal decomposition method has been used for simulation of unsteady incompressible flow fields. after projection of the governing equations along pod modes, a low-dimensional dynamical system is achieved. normally, standard low-dimensional models, due to some reasons, do not predict time variations of flow field accurately. accuracy of dynamical system h...

We introduce a simulation optimization approach that is effective in guiding the search for optimal values of input parameters to a simulation model. Our proposed approach, which includes enhanced data mining methodology and state-of-the-art optimization technology, is applicable to settings in which a large amount of data must be analyzed in order to discover relevant relationships. Our approa...

An approach to the use of simulation and visualization of discrete event oriented simulation models for multi criteria scheduling optimization with genetic algorithms is described. A simulation model was used for fitness function computation of genetic algorithms’ results as well as for visual representation of process behavior of the chosen schedule after genetic algorithm optimization. In thi...

Simulation software can be an effective tool to analyze and optimize process based operations. This abstract details the implementation of a warehouse simulation using the Simcad Pro dynamic simulation environment and its integrated data connectivity. The validated simulation model is then transformed to a real-time system providing live visibility, tracking, and real-time optimization of the w...