Search results for " optimization."
showing 10 items of 2333 documents
Gradient-based shape optimisation of ultra-wideband antennas parameterised using splines
2010
Methodology enabling the gradient-based optimisation of antennas parameterised using B-splines is presented. Use of the spline parametrisation allows us to obtain versatile new shapes, whereas the geometry can be represented with a small set of design variables. Moreover, good control over admissible geometries is retained. Advantages of gradient-based optimisation methods are quick convergence, and the fact that the obtained design can be guaranteed to be a local optimum. Focus of this study is to present techniques that enable the computation of exact gradients of the discrete problem, even though the complexity of the geometries does not permit establishing analytical expressions for the…
Stability Analysis of Large Scale Networks of Autonomous Work Systems with Delays
2011
This paper considers the problem of stability analysis for a class of production networks of autonomous work systems with delays in the capacity changes. The system under consideration does not share information between work systems and the work systems adjust capacity with the objective of maintaining a desired amount of local work in progress (WIP). Attention is focused to derive explicit sufficient delay-dependent stability conditions for the network using properties of matrix norm. Finally, numerical results are provided to demonstrate the proposed approach.
Solution to nonlinear MHDS arising from optimal growth problems
2011
Abstract In this paper we propose a method for solving in closed form a general class of nonlinear modified Hamiltonian dynamic systems (MHDS). This method is used to analyze the intertemporal optimization problem from endogenous growth theory, especially the cases with two controls and one state variable. We use the exact solutions to study both uniqueness and indeterminacy of the optimal path when the dynamic system has not a well-defined isolated steady state. With this approach we avoid the linearization process, as well as the reduction of dimension technique usually applied when the dynamic system offers a continuum of steady states or no steady state at all.
On the evaluation of the global heat transfer coefficient in cutting
2007
The use of numerical simulations for investigating machining processes is remarkably increasing because of the simulation cost is lower than the experiments and the possibility to analyze local variables such as pressures, strains, and temperatures is allowable. Process simulation is very hard from a computational point of view, since it frequently requires remeshing phases and very small time steps. As a consequence, the simulated cutting time is usually of the order of few milliseconds and no steady cutting conditions are generally achieved, at least as far as thermal conditions are concerned. Therefore, nowadays numerical prediction of cutting temperatures cannot be considered fully reli…
Optimal Impulse Control When Control Actions Have Random Consequences
1997
We consider a generalised impulse control model for controlling a process governed by a stochastic differential equation. The controller can only choose a parameter of the probability distribution of the consequence of his control action which is therefore random. We state optimality results relating the value function to quasi-variational inequalities and a formal optimal stopping problem. We also remark that the value function is a viscosity solution of the quasi-variational inequalities which could lead to developments and convergence proofs of numerical schemes. Further, we give some explicit examples and an application in financial mathematics, the optimal control of the exchange rate…
Hedging of Spatial Temperature Risk with Market-Traded Futures
2011
The main objective of this work is to construct optimal temperature futures from available market-traded contracts to hedge spatial risk. Temperature dynamics are modelled by a stochastic differential equation with spatial dependence. Optimal positions in market-traded futures minimizing the variance are calculated. Examples with numerical simulations based on a fast algorithm for the generation of random fields are presented.
A novel technique for stochastic root-finding: Enhancing the search with adaptive d-ary search
2017
The most fundamental problem encountered in the field of stochastic optimization, is the Stochastic Root Finding (SRF) problem where the task is to locate an unknown point x∗ for which g(x∗) = 0 for a given function g that can only be observed in the presence of noise [15]. The vast majority of the state-of-the-art solutions to the SRF problem involve the theory of stochastic approximation. The premise of the latter family of algorithms is to oper ate by means of so-called “small-step”processesthat explorethe search space in a conservative manner. Using this paradigm, the point investigated at any time instant is in the proximity of the point investigated at the previous time instant, render…
Approximation-Based Adaptive Fuzzy Tracking Control for a Class of Nonstrict-Feedback Stochastic Nonlinear Time-Delay Systems
2015
This paper focuses on the problem of approximation-based adaptive fuzzy tracking control for a class of stochastic nonlinear time-delay systems with a nonstrict-feedback structure. A variable separation approach is introduced to overcome the design difficulty from the nonstrict-feedback structure. Mamdani-type fuzzy logic systems are utilized to model the unknown nonlinear functions in the process of controller design, and an adaptive fuzzy tracking controller is systematically designed by using a backstepping technique. It is shown that the proposed controller guarantees that all signals in the closed-loop system are fourth-moment semiglobally uniformly ultimately bounded, and the tracking…
Average flow constraints and stabilizability in uncertain production-distribution systems
2009
We consider a multi-inventory system with controlled flows and uncertain demands (disturbances) bounded within assigned compact sets. The system is modelled as a first-order one integrating the discrepancy between controlled flows and demands at different sites/nodes. Thus, the buffer levels at the nodes represent the system state. Given a long-term average demand, we are interested in a control strategy that satisfies just one of two requirements: (i) meeting any possible demand at each time (worst case stability) or (ii) achieving a predefined flow in the average (average flow constraints). Necessary and sufficient conditions for the achievement of both goals have been proposed by the aut…
Solving the Discrete Multiple Criteria Problem using Convex Cones
1984
An interactive method employing pairwise comparisons of attainable solutions is developed for solving the discrete, deterministic multiple criteria problem assuming a single decision maker who has an implicit quasi-concave increasing utility (or value) function. The method chooses an arbitrary set of positive multipliers to generate a proxy composite linear objective function which is then maximized over the set of solutions. The maximizing solution is compared with several solutions using pairwise judgments asked of the decision maker. Responses are used to eliminate alternatives using convex cones based on expressed preferences, and then a new set of weights is found that satisfies the i…