Search results for "Adaptive optimization"
showing 3 items of 3 documents
An Adaptive Metamodel-Based Optimization Approach for Vehicle Suspension System Design
2014
Published version of an article in the journal: Mathematical Problems in Engineering. Also available from the publisher at: http://dx.doi.org/10.1155/2014/965157 The performance index of a suspension system is a function of the maximum and minimum values over the parameter interval. Thus metamodel-based techniques can be used for designing suspension system hardpoints locations. In this study, an adaptive metamodel-based optimization approach is used to find the proper locations of the hardpoints, with the objectives considering the kinematic performance of the suspension. The adaptive optimization method helps to find the optimum locations of the hardpoints efficiently as it may be unachie…
A New Dynamic Model for Anticipatory Adaptive Control of Airline Seat Reservation via Order Statistics of Cumulative Customer Demand
2017
This paper deals with dynamic anticipatory adaptive control of airline seat reservation for the stochastic customer demand that occurs over time T before the flight is scheduled to depart. It is assumed that time T is divided into m periods, namely a full fare period and m−1 discounted fare periods. The fare structure is given. An airplane has a seat capacity of U. For the sake of simplicity, but without loss of generality, we consider (for illustration) the case of nonstop flight with two fare classes (business and economy). The proposed policies of the airline seat inventory control are based on the use of order statistics of cumulative customer demand, which have such properties as bivar…
Cross-entropy-based adaptive optimization of simulation parameters for Markovian-driven service systems
2005
Abstract Markov fluid models represent a general description of the process of service request arrivals to service systems. The solution of performance analysis problems incorporating them often calls for a simulation approach, for which a reference methodology is Importance Sampling. However, in this case the appropriate choice of the biasing conditions is a problem in itself. In this paper an iterative method based on the cross-entropy is proposed for this choice. The equations are given that allow to derive the biasing conditions from the simulation itself. The application of the proposed method to three different sample cases, referring to one transient scenario (finite time horizon and…