A new evolutionary algorithm for constrained optimization problems

To solve single-objective constrained optimization problems,a new population-based evolutionary algorithm with elite strategy(PEAES) is proposed with the concept of single and multi-objective optimization.Constrained functions are combined to be an objective function.During the evolutionary process,the current optimal solution is found and treated as the reference point to divide the population into three sub-populations:one feasible and two infeasible ones.Different evolutionary operations of single or multi-objective optimization are respectively performed in each sub-population with elite strategy.Thirteen famous benchmark functions are selected to evaluate the performance of PEAES in comparison of other three optimization methods.The results show the proposed method is valid in efficiency,precision and probability for solving single-objective constrained optimization problems.

AN SQP ALGORITHM WITH NONMONOTONE LINE SEARCHFOR GENERAL NONLINEAR CONSTRAINED OPTIMIZATION PROBLEM

In this paper, an SQP type algorithm with a new nonmonotone line search technique for general constrained optimization problems is presented. The new algorithm does not have to solve the second order correction subproblems for each iterations, but still can circumvent the so-called Maratos effect. The algorithm’s global convergence and superlinear convergent rate have been proved. In addition,we can prove that, after a few iterations, correction subproblems need not be solved,so computation amount of the algorithm will be decreased much more. Numericalexperiments show that the new algorithm is effective.

A Robust Video Watermarking Scheme with Squirrel Search Algorithm

Advancement in multimedia technology has resulted in protection against distortion,modification,and piracy.For implementing such protection,we have an existing technique called watermarking but obtaining desired distortion level with sufficient robustness is a challenging task for watermarking in multimedia applications.In the paper,we proposed a smart technique for video watermarking associating meta-heuristic algorithms along with an embedding method to gain an optimized efficiency.The main aim of the optimization algorithm is to obtain solutions with maximum robustness,and which should not exceed the set threshold of quality.To represent the accuracy of the proposed scheme,we employ a popular video watermarking technique(DCT domain)having frame selection and embedding method for watermarking.A squirrel search algorithm is chosen as a meta-heuristic algorithm that utilizes the stated fitness function.The results indicate that quality constraint is fulfilled,and the proposed technique gives improved robustness against different attacks with several quality thresholds.The proposed technique could be practically implemented in several multimedia applications such as the films industry,medical imagery,OOT platforms,etc.

Superconvergence of Rectangular Mixed Finite Element Methods for Constrained Optimal Control Problem

We investigate the superconvergence properties of the constrained quadratic elliptic optimal control problem which is solved by using rectangular mixed finite element methods.We use the lowest order Raviart-Thomas mixed finite element spaces to approximate the state and co-state variables and use piecewise constant functions to approximate the control variable.We obtain the superconvergence of O(h^(1+s))(0<s≤1)for the control variable.Finally,we present two numerical examples to confirm our superconvergence results.