The lane reversal has proven to be a useful method to mitigate traffic congestion during rush hour or in case of specific events that affect high traffic volumes. In this work we propose a methodology that is placed within optimization via Simulation, by means of which a multi-objective genetic algorithm and simulations of traffic are used to determine the configuration of ideal lane reversal. ...

the bubble effectiveness in liquid phase cylohexane non-catalytic oxidation process is discussed in this paper. then the bubble effectiveness and a new proposed kinetic model are used in the mathematical model of the industrial reactor for the cyclohexane non-catalytic oxidation process. furthermore, simulation and optimization based on this reactor model are carried out. the results of simulat...

In this paper a novel modelling and solving method has been developed to address the so-called resource constrained project scheduling problem (RCPSP) where project tasks have multiple modes and also the preemption of activities are allowed. To solve this NP-hard problem, a new general optimization via simulation (OvS) approach has been developed which is the main contribution of the current re...

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...

This paper presents a new observer design methodology for a time varying actuator fault estimation. A new linear matrix inequality (LMI) design algorithm is developed to tackle the limitations (e.g. equality constraint and robustness problems) of the well known so called fast adaptive fault estimation observer (FAFE). The FAFE is capable of estimating a wide range of time-varying actuator fault...

in this paper, the application of neural networks for simulation and optimization of the cogeneration systems has been presented. cgam problem, a benchmark in cogeneration systems, is chosen as a casestudy. thermodynamic model includes precise modeling of the whole plant. for simulation of the steadysate behavior, the static neural network is applied. then using dynamic neural network, plant is...

Dow AgroSciences has improved its bottom line by using simulation-based optimization to reduce the time and expense of moving a portfolio of products to market. We examined mathematical programming approaches for scheduling new-product development but found that the solution of these formulations is intractable for problems of practical size that include resource constraints. We developed a sim...

In this paper, we develop a simulation optimization algorithm for determining the traffic light signal timings for an intersection of two one-way street traffic flows modeled as single-server queues. The system performance is estimated via stochastic discreteevent simulation, and gradient-based search based on stochastic approximation is applied. In particular, we use smoothed perturbation anal...