The design of truthful auctions that approximate the optimal expected revenue is a central problem in algorithmic mechanism design. 30 years after Myerson’s characterization of Bayesian optimal auctions in single-parameter domains [9], characterizing but also providing efficient mechanisms for multi-parameter domains still remains a very important unsolved problem. Our work improves upon recent...

This paper presents the usage of a multi-objective genetic algorithm to a set of engineering design problems. The studied problems span from detailed design of a hydraulic pump to more comprehensive system design. Furthermore, the problems are modeled using dynamic simulation models, response surfaces based on FE–models as well as static equations. The proposed method is simple and straight for...

the problem of hypothesis testing with a nuisance parameter is considered. two methods forusing fuzzy knowledge on the nuisance parameter to test hypotheses are suggested. these methods areneither a pure classical nor a pure bayesian approach to hypothesis testing, but rather related to both. afew known examples and their applications, which cannot be studied by the parametric statisticalmethod...

centralizing and using proper transportation facilities cut down costs and traffic. hub facilities concentrate on flows to cause economic advantage of scale and multimodal transportation helps use the advantage of another transporter. a distinctive feature of this paper is proposing a new mathematical formulation for a three-stage p-hub location routing problem with simultaneous pick-ups and de...

In this paper, the first and second order approximations of Taylor expansion are used for calculating the change of each natural frequency by modifying an arbitrary parameter of a system with a known amount and based on this approximation, the inverse eigenvalue problem is transformed to a solvable algebraic equation. The finite element formulation, based on the classical laminated plate theory...

In this paper, a framework for the simplification and standardization of metaheuristic related parameter-tuning by applying a four phase methodology, utilizing Design of Experiments and Artificial Neural Networks, is presented. Metaheuristics are multipurpose problem solvers that are utilized on computational optimization problems for which no efficient problem specific algorithm exist. Their s...

In this paper, we formulate the feasibility problem corresponding to a filter design problem as a convex optimization problem. Combined with a bisection rule this leads to an algorithm of minimizing the design parameter in the filter design problem. A safety margin is introduced to solve the numerical difficulties when solving this type of problems numerically. The numerical experiments illustr...

We consider the problem of state and parameter estimation for a class of nonlinear oscillators defined as a system of coupled nonlinear ordinary differential equations. Observable variables are limited to a few components of state vector and an input signal. This class of systems describes a set of canonic models governing the dynamics of evoked potential in neural membranes, including Hodgkin-...