Davide Cherubini - PhD Thesis - UniCA Eprints

Chapter 4Optimization MethodsThis chapter describes different typical approaches to optimization methods, namelyheuristic and deterministic algorithms. At the end of the chapter the techniquesused in the present dissertation are briefly introduced. A wide and detailed explanationwill be furnished in the next chapters.4.1 Heuristic AlgorithmsThe term heuristic is used for those algorithms that look for feasible solutionsamong all possible ones, but that do not guarantee the optimality of the solutionfound. In fact, a heuristic method usually finds good solutions lying very closeto the optima and runs reasonably quickly. Unfortunately, there is no argumentthat this will always be the case.With the term meta-heuristic a class of general heuristic methods is indicated,which can be applied to a wide range of computational problems by combiningheuristics. Meta-heuristics are generally applied to problems for which it does notexist a specific algorithm or heuristic, or simply when it is not useful to implementsuch a method.The goal of heuristic and meta-heuristic optimization algorithms, is to findthe combination of input parameters (state) among all possible solution (searchspace), which minimizes (or maximizes) a specific function (objective or goalfunction). Variants and “hybrids” of heuristic techniques have been proposed inliterature, applying them to specific complex problems. As shown in Chapter 3,19