A Robust Simulation-based Multicriteria Optimization Methodology
نویسنده
چکیده
This paper describes a methodology for solving Parameter Design (PD) problems in production and business systems of considerable complexity. The solution is aimed at determining optimum settings to system critical parameters so that each system response is at its optimum performance level with least amount of variability. When approaching such problem, analysts are often faced with four major challenges: representing the complex parameter design problem, utilizing an effective search method that is able to explore the problem’s complex and large domain, making optimization decisions based on multiple and, often, conflicting objectives, and handling the stochastic variability of in system response as an integral part of the search method. to tackle such challenges, this paper proposes a solution methodology that integrates four state-of-the-art modules of proven methods: Simulation Modeling (SM), Genetic Algorithm (GA), Entropy Method (EM), and Robustness Module (RM).
منابع مشابه
A Robust Adaptive Observer-Based Time Varying Fault Estimation
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...
متن کاملReliability-Based Robust Multi-Objective Optimization of Friction Stir Welding Lap Joint AA1100 Plates
The current paper presents a robust optimum design of friction stir welding (FSW) lap joint AA1100 aluminum alloy sheets using Monte Carlo simulation, NSGA-II and neural network. First, to find the relation between the inputs and outputs a perceptron neural network model was obtained. In this way, results of thirty friction stir welding tests are used for training and testing the neural network...
متن کاملOn Robust Optimization - Relations Between Scalar Robust Optimization and Unconstrained Multicriteria Optimization
We introduce an unconstrained multicriteria optimization problem and discuss its relation to various well-known scalar robust optimization problems with a finite uncertainty set. Specifically, we show that a unique solution of a robust optimization problem is Pareto optimal for the unconstrained optimization problem. Furthermore, it is demonstrated that the set of weakly Pareto optimal solution...
متن کاملRobust Coordinated Design of UPFC Damping Controller and PSS Using Chaotic Optimization Algorithm
A Chaotic Optimization Algorithm (COA) based approach for the robust coordinated design of the UPFC power oscillation damping controller and the conventional power system stabilizer has been investigated in this paper. Chaotic Optimization Algorithms, which have the features of easy implementation, short execution time and robust mechanisms of escaping from local optimum, is a promising tool fo...
متن کاملA Robust Optimization Methodology for Multi-objective Location-transportation Problem in Disaster Response Phase under Uncertainty
This paper presents a multi-objective model for location-transportation problem under uncertainty that has been developed to respond to crisis. In the proposed model, humanitarian aid distribution centers (HADC), the number and location of them, the amount of relief goods stored in distribution centers, the amount of relief goods sent to the disaster zone, the number of injured people transferr...
متن کامل