Optimization-simulation technology is developed simultaneously with progress in numeric methods, computer science and different fields of modern mathematics. This paper gives the list of problems, which are formulated and successfully solved, and two primers of numeric procedures for decision of multiparameter multicriteria optimization problem. Iterative procedure for structural grows of large...

To help disaster response organizations improve the management of regional emergency assets and operations, we propose to interface an agent-based, discrete event simulator with a geographic information system and a rule base (describing standard policies and protocols for various disaster responses). The system architecture will enable modules to dynamically “talk” with each other by exchangin...

Reliable forecasts of influenza can aid in the control of both seasonal and pandemic outbreaks. We introduce a simulation optimization (SIMOP) approach for forecasting the influenza epidemic curve. This study represents the final step of a project aimed at using a combination of simulation, classification, statistical and optimization techniques to forecast the epidemic curve and infer underlyi...

For multi-objective optimal reactive power dispatch (MORPD), a new approach is proposed where simultaneous minimization of the active power transmission loss, the bus voltage deviation and the voltage stability index of a power system are achieved. Optimal settings of continuous and discrete control variables (e.g. generator voltages, tap positions of tap changing transformers and the number of...

In this paper, we propose an ordinal optimization approach to solve for a good enough solution of the stochastic simulation optimization problem with huge decision-variable space. We apply the proposed ordinal optimization algorithm to G/G/1/K polling systems to solve for a good enough number-limited service discipline to minimize the weighting average waiting time. We have compared our results...

Simulation optimization is providing solutions to important practical problems previously beyond reach. This paper explores how new approaches are significantly expanding the power of simulation optimization for managing risk. Recent advances in simulation optimization technology are leading to new opportunities to solve problems more effectively. Specifically, in applications involving risk an...

One of the key issues in mining is the hauling system. Truck and shovels are the most widely used transportation equipment in mines. In this paper, a two-phase simulation-based optimization is presented to maximize utilization of hauling system in the largest Iranian open-pit copper mine. In the first phase, The OptQuest for Arena software package was used to solve the optimization problem to p...

Developing optimal flocking control procedure is an essential problem in mobile sensor networks (MSNs). Furthermore, finding the parameters such that the sensors can reach to the target in an appropriate time is an important issue. This paper offers an optimization approach based on metaheuristic methods for flocking control in MSNs to follow a target. We develop a non-differentiable optimizati...

In this paper, we consider a stochastic Time-Cost Tradeoff Problem (TCTP) in PERT networks for project management, in which all activities are subjected to a linear cost function and assumed to be exponentially distributed. The aim of this problem is to maximize the project completion probability with a pre-known deadline to a predefined probability such that the required additional cost is min...

This chapter is a continuation of our chapters “Simulation Optimization Via Metamodeling Approach” and “Simulation Optimization For Finite Parameter Space” found elsewhere in this volume. In this chapter, we investigate gradientbased simulation optimization (GBSO) methods, including Perturbation Analysis (PA), Likelihood Ratio (LR), Finite Difference (FD), and Frequency Domain Analysis (FDA). W...