Constrained cohort intelligence using static and dynamic penalty function approach for mechanical components design

Constrained Cohort Intelligence using Static and Dynamic Penalty Function Approach for Mechanical Components Design

Most of the metaheuristics can efficiently solve unconstrained problems; however, their performance may degenerate if the constraints are involved. This paper proposes two constraint handling approaches for an emerging metaheuristic of Cohort Intelligence (CI). More specifically CI with static penalty function approach (SCI) and CI with dynamic penalty function approach (DCI) are proposed. The ...

Constrained Evolutionary Optimization - the penalty function approach

Penalty Function Approach for Constrained Convolutive Blind Source Separation

A new approach for convolutive blind source separation (BSS) using penalty functions is proposed in this paper. Motivated by nonlinear programming techniques for the constrained optimization problem, it converts the convolutive BSS into a joint diagonalization problem with unconstrained optimization. Theoretical analyses together with numerical evaluations reveal that the proposed method not on...

OPTIMUM DESIGN OF FILAMENT–WOUND LAMINATED CONICAL SHELLS FOR BUCKLING USING THE PENALTY FUNCTION

Optimum laminate configuration for minimum weight of filament–wound laminated conical shells subject to buckling load constraint is investigated. In the case of a laminated conical shell the thickness and the ply orientation (the design variables) are functions of the shell coordinates, influencing both the buckling load and its weight. These effects complicate the optimization problem consider...

statistical inference via empirical bayes approach for stationary and dynamic contingency tables

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