A highly competitive micro evolutionary algorithm to solve unconstrained optimization problems called μJADE (micro adaptive differential evolution), is adapted to deal with constrained search spaces. Two constraint-handling techniques (the feasibility rules and the ε-constrained method) are tested in μJADE and their performance is analyzed. The most competitive version is then compared against ...

in this context, a novel structure has been proposed for simple differential evolutionary (de) algorithm to solve optimal recloser placement. for this, an operator is added to de algorithm to adapt concept of the problem. other contribution of this work is formulating a novel objective function. the proposed objective function has been formulated to improve four reliability indices which consis...

the vast use of linear prediction coefficients (lpc) in speech processing systems has intensified the importance of their accurate computation. this paper is concerned with computing lpc coefficients using evolutionary algorithms: genetic algorithm (ga), particle swarm optimization (pso), dif-ferential evolution (de) and particle swarm optimization with differentially perturbed velocity (pso-dv...

this paper proposes a novel hybrid algorithm namely apso-bfo which combines merits of bacterial foraging optimization (bfo) algorithm and adaptive particle swarm optimization (apso) algorithm to determine the optimal pid parameters for control of nonlinear systems. to balance between exploration and exploitation, the proposed hybrid algorithm accomplishes global search over the whole search spa...

In this study, weight optimization of the prismatic core sandwich panel under transverse and longitudinal loadings has been independently investigated. To solve the optimization problems corresponding to the mentioned loadings, a new Improved Constrained Differential Evolution (ICDE) algorithm based on the multi-objective constraint handling method is implemented. The constraints of the problem...

the multiple traveling salesman problem (mtsp) is a generalization of the famous traveling salesman problem (tsp), where more than one salesman is used in the solution. although the mtsp is a typical kind of computationally complex combinatorial optimization problem, it can be extended to a wide variety of routing problems. this paper presents an efficient and evolutionary optimization algorith...

Hongyuan Gao*,Shibo Zhang,Ming Diao, and Yanan Du College of Information and Communication Engineering Harbin Engineering University Harbin, P. R. China [email protected], [email protected], diaoming@ hrbeu.edu.cn,[email protected] Abstract—It is a classical integer optimization difficulty to design optimal selection scheme in cooperative relay networks considering co-channel interfer...

Heuristic evolutionary optimization algorithms are the solutions to many engineering optimization problems. Differential evolution (DE) is a real stochastic evolutionary parameter optimization in current use.DE does not require more control parameters compared to other evolutionary algorithms. Master Production Scheduling (MPS) is posed as one of multi objective parameter optimization problems ...

A number of algorithms based on the evolutionary processing have been proposed forcommunication networks backbone such as Genetic Algorithm (GA). However, there has beenlittle work on the SWARM optimization algorithms such as Particle Swarm Optimization(PSO) for backbone topology design. In this paper, the performance of PSO on GA isdiscussed and a new algorithm as PSOGA is proposed for the net...