This paper presents an improved Differential Evolution algorithm (IDE). It is aimed at improving its performance in estimating the relevant parameters for metabolic pathway data to simulate glycolysis pathway for yeast. Metabolic pathway data are expected to be of significant help in the development of efficient tools in kinetic modeling and parameter estimation platforms. Nonetheless, due to t...

Production scheduling problems and traditional differential evolution(DE) are analyzed in this paper. Taking the minimum of total completion time as the objective function of production scheduling, a production scheduling model is established for batch processes in process industry.Considering that the performance of the traditional DE algorithm is sensitive to the parameter settings,an adaptiv...

Since the introduction of Ant Colony Optimization (ACO) technique in 1992, the algorithm starts to gain popularity due to its attractive features. However, several shortcomings such as slow convergence and stagnation motivate many researchers to stop further implementation of ACO. Therefore, in order to overcome these drawbacks, ACO is proposed to be combined with Differential Evolution (DE) an...

A clustering algorithm using the framework of membrane computing is proposed in this paper. The P system used is a cell-like P system of two-layer nested structure: a skin membrane contains several elementary membranes. Each object in elementary membranes represents a group of cluster centers. Objects in the system evolve by using the differential evolution mechanism, and then the global optima...

Reduction of sidelobe level in concentric ring arrays results in wide first null beamwidth (FNBW). Theauthors propose a pattern synthesis method based on modified Particle Swarm Optimization (PSO) algorithm and Differential Evolution (DE) algorithm to reduce sidelobe level while keeping the first null beamwidth (FNBW) fixed or variable. This is achieved by optimizing both ring spacing and numbe...

The ε constrained method is an algorithm transformation method, which can convert algorithms for unconstrained problems to algorithms for constrained problems using the ε level comparison, which compares search points based on the pair of objective value and constraint violation of them. We have proposed the ε constrained differential evolution εDE, which is the combination of the ε constrained...

Electric power providing companies has to deliver reliable electric power in quality and at minimum cost for the competition in deregulated environment. To know the power system security and operating state, power flows in lines and bus voltage magnitude and angle are calculated using power flow analysis, and to tune the power system for minimum operating cost while ensure security and reliabil...

Differential evolution algorithm is a simple yet efficient metaheuristic for global optimization over continuous spaces. However, there is a shortcoming of premature convergence in standard DE, especially in DE/best/1/bin. In order to take advantage of direction guidance information of the best individual of DE/best/1/bin and avoid getting into local trap, based on multiple mutation strategies,...

In this article, we introduce an improved optimization based technique for the synthesis of circular antenna array. The main objective is to achieve minimum side lobe levels, maximum directivity and null control for the non-uniform, planar circular antenna array. The design procedure utilizes an improved variant of a prominent and efficient metaheuristic algorithm of current interest, namely th...

A multi-objective differential evolution algorithm based on adaptive mutation strategies and partition selected search is proposed based on classical differential evolution (DE) to further improve the convergence and diversity of multi-objective optimization problems. This algorithm improves mutation operation in DE, makes search oriented and ensures the convergence of algorithm by adaptively s...