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We consider the problem of determining the optimal policy for staffing a queueing system over multiple periods, using a model that takes into account transient queueing effects. Formulating the problem in a dynamic programming ...

A new approach to optimal decoupling for multi-input multi-output (MIMO), linear, time-invariant control systems, is presented. This general optimal decoupling method is based on the minimization of componentwise performance ...

Design and optimization of planar leg mechanisms featuring symmetrical foot-point paths are presented in this study. These leg mechanisms are designed in such a way that a corresponding walking machine has the flexibility ...

A physically-based dynamic simulator has been constructed to investigate the time-dependent behavior of equipment process, sensor, and control system for rapid thermal chemical vapor deposition (RTCVD) of polysilicon from ...

In the semiconductor manufacturing industry, optimization of advanced equipment and process designs must include both manufacturing metrics (such as cycle time, consumables cost, and product quality) and environmental ...

ADIFFSQP is a utility program that allows to user of the FFSQP[1] constrained nonlinear optimization routines to invoke the computational differentiation (or automatic differentiation:AD) preprocessor ADIFOR2.0 [2] conveniently

Many run-to-run (RtR) control methods have been developed in recentyears. Two particular set-valued RtR control schemes based on the Dasgupta-Huang OptimalBounded Ellipsoid (DHOBE) algorithm are introduced. Compared to ...

The guided random search techniques, genetic algorithms and simulated annealing, are very promising strategies, and both techniques are analogs from physical and biological systems. Through genetic algorithms, the simulation ...

In this dissertation, a novel parallel manipulator is investigated. The manipulator has three degrees of freedom and the moving platform is constrained to only translational motion. The main advantages of this parallel ...

This paper describes a two-space genetic algorithm that finds solutions to minimax optimization problems. The genetic algorithm maintains two populations and searches both simultaneously. Each individual is evaluated with ...