Optimization problems were and still are the focus of mathematics from antiquity to the
present. Since the beginning of our civilization, the human race has had to confront …

In this paper, a hybrid gradient simulated annealing algorithm is guided to solve the
constrained optimization problem. In trying to solve constrained optimization problems using …

The goal of this work is to propose a hybrid algorithm called real-coded self-organizing
migrating genetic algorithm by combining real-coded genetic algorithm (RCGA) and self …

Network routers occupy a key role in modern data transport and consequently are attractive
targets for attackers. By manipulating, diverting or dropping packets arriving at a …

Peak detection is an important preprocessing step in the analysis of mass spectrometry data.
Currently, most peak detection methods have limited identification ability when there are …

This paper applies a genetic algorithm with hierarchically structured population to solve
unconstrained optimization problems. The population has individuals distributed in several …

A new hybrid gradient simulated annealing algorithm is introduced. The algorithm is
designed to find the global minimizer of a nonlinear function of many variables. The function …

Nonlinear constrained optimal trajectory planning is a challenging and fundamental area of
research. This paper proposes bio-inspired fast-time approaches for this type of problems …

In this paper, a new Modified Meta-Heuristic algorithm is proposed. This method contains
some modifications to improve the performance of the simulated-annealing algorithm (SA) …

This book is devoted to the presentation of an exact quadratic regularization method for
solving the problems of global optimization. The essence of this method is to transform …