Comparison of Heuristic and Metaheuristic Algorithms

Abstract

The development of computer technologies day by day has enabled the use of new technological approaches in solving many problems. Technological innovations are used to solve many problems, especially thanks to hardware devices that develop in capacity, and algorithms that continue to develop rapidly. These technologies are used to provide significant time and/or performance gains in solving problems. The great change in software technologies has led to the emergence of many smart algorithms. With the development of artificial intelligence approaches, algorithms inspired by many nature and natural events have been used in the solution stages of problems. These approaches, which take the intuitive movements of living things as an example, have revealed a new solution approach in addition to the mathematical and statistical models used for problem-solving. These algorithms, which are called heuristic algorithms, aim to create the most appropriate solution set by considering the time and/or performance gains of the solution sets. The use of these algorithms, which can be used in solving many problems from production to design, from optimization problems to classification problems, is quite common. With the development of heuristic algorithms, new approaches such as meta-heuristic and hyper-heuristic algorithms have been introduced. In our study, a detailed examination has been made of these algorithms, which are classified as heuristic algorithms, and especially heuristic algorithms have been compared with meta-heuristic (meta-heuristic) algorithms, and details on their similarities and differences have been tried to be presented. Algorithms are shown by classifying them according to their structures. In particular, the basic features of heuristic and meta-heuristic algorithms such as search space, performance, workspace, search behaviors, search process, simplicity, reliability, flexibility, and initial requirements have been examined and the similarities and differences between them have been tried to be shown with examples. Information on current algorithms published in recent years and their applicability for solving problems are also given.