This paper proposes a hybrid chemical-reaction optimization (HCRO) algorithm for solving the job-shop scheduling problem with fuzzy processing time. The flexible maintenance activities under both resumable and non-resumable situations are also considered to make the problem more close to the reality. In the proposed algorithm, each solution is represented by a chemical molecule. Four elementary...

When applying optimizations, a number of decisions are made using fixed strategies, such as always applying an optimization if it is applicable, applying optimizations in a fixed order and assuming a fixed configuration for optimizations such as tile size and loop unrolling factor. In this paper, we present a framework that enables these decisions to be made based on predicting the impact of an...

We analyze the global convergence properties of some variants of regularized continuous Newton methods for convex optimization and monotone inclusions in Hilbert spaces. The regularization term is of LevenbergMarquardt type and acts in an open-loop or closed-loop form. In the open-loop case the regularization term may be of bounded variation.

This paper proposes a novel optimization technique for the closed-loop controller design of a boost type DC-DC converter based on the Particle Swarm Optimization (PSO) algorithm. The design of the closedloop control parameters is framed as an optimization task such that the PSO algorithm can identify the controller parameters. An appropriate fitness function is then derived for the required obj...

Optimization of specific power of axial flux permanent magnet brushless DC (PMBLDC) motor based on genetic algorithm optimization technique for an electric vehicle application is presented. Double rotor sandwiched stator topology of axial flux permanent magnet brushless DC motor is selected considering its best suitability in electric vehicle applications. Rating of electric motor is determined...

In this paper, a general framework for image contrast enhancement algorithm based on an optimization problem is presented. Through this optimization, the intensities can be better distributed. The algorithm is based on the facts that the histogram of the enhanced image is close to the input image histogram and uniform distribution, simultaneously. Based on this fact, we obtain a closed form opt...

We develop a ytopt autotuning framework that leverages Bayesian optimization to explore the parameter space search and compare four different supervised learning methods within evaluate their effectiveness. select six of most complex PolyBench benchmarks apply newly developed LLVM Clang/Polly loop pragmas optimize them. then use pragma parameters improve performance. The experimental results sh...

This paper proposes a new design optimization method for structures subject to uncertainty. Interval model is used to account for uncertainties of uncertain-but-bounded parameters. It only requires the determination of lower and upper bounds of an uncertain parameter, without necessarily knowing its precise probability distribution. The interval uncertain optimization problem will be formulated...

This paper tackles the disturbances in control operation in close-loop and its effect on the system by studding transfer function in presence and absence of disturbances. An example controlling a mechanical system is taken and the unexpected outside element effect consider here as disturbance, the close-loop feedback transfer function of the system. The model of the mechanical system is showing...

Jingling Xue Department of Mathematics, Statistics and Computing Science University of New England, Armidale 2351, Australia ABSTRACT This paper is a follow-up to Irigoin and Triolet's earlier work and our recent work on tiling. In this paper, tiling is discussed in terms of its e ects on the dependences between tiles, the dependenceswithin a tile and the required dependence test for legality. ...