Different constraint handling techniques have been used with multiobjective evolutionary algorithms (MOEA) to solve constrained multiobjective optimization problems. It is impossible for a single constraint handling technique to outperform all other constraint handling techniques always on every problem irrespective of the exhaustiveness of parameter tuning. To overcome this selection problem, ...

1389-1286/$ see front matter 2012 Elsevier B.V http://dx.doi.org/10.1016/j.comnet.2012.03.019 ⇑ Corresponding author. E-mail address: [email protected] (G. The placement of wavelength converters in an arbitrary mesh network is known to belong to the class of NP-complete problems. So far, this problem has been solved by heuristic strategies or by the application of optimization tools suc...

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...

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 Economic Load Dispatch (ELD) problems in power generation systems are to reduce the fuel cost by reducing the total cost for the generation of electric power. This paper presents an efficient Modified Firefly Algorithm (MFA), for solving ELD Problem. The main objective of the problems is to minimize the total fuel cost of the generating units having quadratic cost functions subjected to lim...

Although important contributions have been made in recent years within the field of bioprocess model development and validation, in many cases the utility of even relatively good models for process optimization with current state-of-the-art algorithms (mostly offline approaches) is quite low. The main cause for this is that open-loop fermentations do not compensate for the differences observed ...

Although a number of multiobjective evolutionary algorithms have been proposed over the last two decades, not much effort has been made to deal with variable linkages in multiobjective optimization. Recently, we have suggested a general framework of multiobjective evolutionary algorithms based on decomposition (MOEA/D) [1]. MOEA/D decomposes a MOP into a number of scalar optimization subproblem...

In this paper, a novel recombination operator, called adaptive hybrid crossover operator (AHX), is designed for tackling continuous multiobjective optimization problems (MOPs), which works effectively to enhance the search capability of multiobjective evolutionary algorithms (MOEAs). Different from the existing hybrid operators that are commonly operated on chromosome level, the proposed operat...

Evolutionary algorithms (EAs) are population-based global search methods. They have been successfully applied to many complex optimization problems. However, EAs are frequently incapable of finding a convergence solution in default of local search mechanisms. Memetic Algorithms (MAs) are hybrid EAs that combine genetic operators with local search methods. With global exploration and local explo...

A novel version of Ant Colony Optimization (ACO) algorithms for solving continuous space problems is presented in this paper. The basic structure and concepts of the originally reported ACO are preserved and adaptation of the algorithm to the case of continuous space is implemented within the general framework. The stigmergic communication is simulated through considering certain direction vect...