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Any large functioning system consists of equipment that needs to be repaired during its lifetime. The methods of mathematical programming are used to formalize the optimization problem of preventive equipment repair planning in this paper. The method is used to find the annual optimal plan of preventive equipment repair. The goal of such plan is the uniform distribution of repair works by the months. It is supposed, that the deviation from the standard plan of repair works can not be more than one month. An algorithm to find the optimal plan of repair works is provided. A numerical example is given. [ABSTRACT FROM AUTHOR]

In the last years a great interest in optimization algorithms aimed to design forming processes was demonstrated by many researches. Proper design methodologies to reduce times and costs have to be developed mostly based on computer aided procedures. Response surface methods (RSM) proved their effectiveness in the recent years also for the application in sheet metal forming aiming to reduce the number of numerical simulations. Actually, the main drawback of such method is the number of direct problem to be solved in order to reach good function approximations. A very interesting aspect in RSM application regards the possibility to build response surfaces basing on moving least squares approximations (MLS) by utilizing a moving and zooming region of interest. In this paper, MLS is utilized to solve an optimization problem for a complex sheet metal forming process. The influence on the optimization results was analyzed basing on MLS peculiarities. In particular, the analysis was carried out studying the effect of weighting functions shape and of the points belonging to the design of experiments. [ABSTRACT FROM AUTHOR]

In this paper we will present an effective numerical method for the Black-Scholes equation with transaction costs for the limiting price u(s, t;a). The technique combines the Rothe method with a two-grid (coarse-fine) algorithm for computation of numerical solutions to initial boundary-values problems to this equation. Numerical experiments for comparison the accuracy ant the computational cost of the method with other known numerical schemes are discussed. [ABSTRACT FROM AUTHOR]

This paper presents a new simulated annealing algorithm to solve constrained multi-global optimization problems. To compute all global solutions in a sequential manner, we combine the function stretching technique with the adaptive simulated annealing variant. Constraint-handling is carried out through a nondifferentiable penalty function. To benchmark our penalty stretched simulated annealing algorithm we solve a set of well-known problems. Our preliminary numerical results show that the algorithm is promising. [ABSTRACT FROM AUTHOR]

A simplified (one step) method called “inverse approach” (IA) for the numerical analysis of the stamping process has been continuously developed by the authors since the end of the eighties. In the present paper we recall the main finite element formulation aspects, for an efficient estimation of the large elastoplastic strains encountered in deep drawing operations. The capabilities of the code Fast_Stamp include: fixed (imposed) initial blank, bending effects due to tool curvatures, blankholder restraining forces (including drawbeads). Considerations of bending and unbending during forming stages can improve the IA regarding stresses distribution. In this case satisfactory estimation of springback can result. Since 1996 we also developed “math based” optimization algorithms and strategies. The cost functions and constraints are mainly expressed to reduce or control the thickness changes, the localized necking, the wrinkling tendency, the springback after forming. The design variables are describing the shape of the blank, the additional (addendum) surfaces, the restraining forces due to drawbeads and the material properties such as anisotropy coefficient and hardening exponent. Optimization algorithms are mainly based on surface response techniques with moving least square approximation and SQP to find the optimum solution at each iteration. Selected results will be presented related to the design of additional surfaces. © 2005 American Institute of Physics [ABSTRACT FROM AUTHOR]

This paper introduces various geometric optimization problems and explores their relationship with motion coordination algorithms for networks of mobile agents. For each problem, the objective is the optimization of an appropriate multi-center function encoding the sensing task to be achieved by the mobile network in a dynamic environment. We present five different scenarios: the expected value scenario, the expected value scenario with limited range interactions, the area scenario, the worst-case scenario and the non-interference scenario. We carefully analyze the smoothness properties and gradient information of the multi-center functions. Based on this investigation, we propose distributed motion coordination algorithms specifically tailored for each scenario. The multi-center functions play the role of network aggregate cost functions certifying the validity of the coordination algorithms. Various numerical simulations illustrate the results. © 2004 American Institute of Physics [ABSTRACT FROM AUTHOR]