“This workshop focuses on complete solving techniques for continuous constraint satisfaction and optimization problems that provide all solutions with full rigor. Less rigorous solution techniques are not excluded, since they may be part of complete relevant techniques. Complete solution techniques guarantee that all the constraints – e.g. security or tolerance criteria – are satisfied and the ...

The multicast routing problem with quality of service (QoS) constraints is a key requirement of computer networks supporting multimedia applications. In order to resolve Qos multicast routing effectively and efficiently, an improved ant colony optimization (ACO) algorithm is proposed to resolve this problem.The core idea of improved ACO algorithm is mainly realized through pheromone local and g...

I propose an axiomatic framework for belief revision when new information is qualitative, of the form “event A at least as likely event B .” My decision maker need not have beliefs about joint distribution signal she will receive and payoff‐relevant states. three axioms, Exchangeability , Stationarity Reduction to characterize class pseudo‐Bayesian updating rules. The key axiom, requires that o...

A finite model updating method that combines dynamic-static long-gauge strain responses is proposed for highway bridge static loading tests. For this method, the objective function consisting of static long-gauge stains and the first order modal macro-strain parameter (frequency) is established, wherein the local bending stiffness, density and boundary conditions of the structures are selected ...

We propose an augmented Lagrangian algorithm for solving large-scale equality constrained optimization problems. The novel feature of the algorithm is an adaptive update for the penalty parameter motivated by recently proposed techniques for exact penalty methods. This adaptive updating scheme greatly improves the overall performance of the algorithm without sacrificing the strengths of the cor...

In this paper, a novel adaptive tracking controller is proposed for mobile robots in presence of wheel slip and external disturbance force based on neural networks with online weight updating laws. The uncertainties due to the wheel slip and external force are compensated online by neural networks in order to achieve the desired tracking performance. The online weight updating laws are modified...

In this paper, we propose a novel boosted mixture learning (BML) framework for Gaussian mixture HMMs in speech recognition. BML is an incremental method to learn mixture models for classification problem. In each step of BML, one new mixture component is calculated according to functional gradient of an objective function to ensure that it is added along the direction to maximize the objective ...

In this study, a flexible optimization approach is introduced to design an optimal biocompatible solvent for an extractive fermentation process with cell-recycling. The optimal process/solvent design problem is formulated as a mixed-integer nonlinear programming model in which performance requirements of the compounds are reflected in the objectives and the constraints. A flexible or fuzzy opti...

This paper describes DIANNER, a Hybrid Distributed Adaptive Neural Router for a communication network based on neural networks. By combining a simple neural network for the routing decision and a rule based system for the updating and learning process, DIANNER can implement more features for the router to quickly respond to more complex and dynamically changing real world environments. Furtherm...