Metaheuristics for Intelligent Electrical Networks

1Single Solution Based Metaheuristics

1.1. Introduction

In daily life, optimizing is a common activity for both individuals and professionals. For example, the process of optimizing involves minimizing production time and expenditure, and maximizing profit and performance. As a result, optimization has become a discipline in itself to solve various problems, particularly in the economic sector [SAM 69], in the field of biology [GOT 82] and in various industries [YOS 00]. To solve these problems, technology is used to implement algorithms that simulate real problems in order to achieve results that will subsequently be used according to the intended purpose. These simulations can be simple but also very complex. The developed algorithms can be accurate or approximated, leading to the global optimum or to a solution closed to the global optimum. The objective of optimization is to find the global and/or the local optimum or optima. Depending on the optimization problem being addressed, one or more methods can be applied, and one of them may be more suitable than the others.

These methods include the class of path-based methods also called single-solution metaheuristics. These methods are algorithms in which the search for the optimum is achieved by manipulating a single solution throughout the progression of the algorithm. From an initial solution, the latter evolves throughout the algorithm following a certain mechanism until the stopping criterion is reached. Furthermore, ...