preview

The Problem And Defining Fitness Function Essay

Decent Essays

. Population based search involves evolution of group of points in search space such as in ant colony optimization and evolutionary computation techniques. The mode of origin is another basis to distinguish between nature inspired and no nature inspired metaheuristic algorithm. Evolutionary computation and Ant Colony Optimization belongs to the class of nature inspired whereas tabu search and iterated local search belongs to the class of non nature inspired algorithms. Metaheuristic algorithms are also known as search based techniques or optimization algorithms which when applied to software engineering problems gave rise to Search Based Software Engineering (SBSE) [3] which reformulates software engineering problems as search problems. It is a collective attempt to shift from human based search to machine based search by applying search based optimization techniques. These methods encompass representation of problem and defining fitness function. SBSE treats search problem as one where optimal or near optimal solution are sought in a search space of solution by making use of fitness function that discriminates worse and better solution. Although many researchers, practitioners have applied search based optimization to software engineering domain, SBSE term was first coined by Harman and Jones [3] in 2001 in their work which advocates Search Based Optimization as a general approach to Software Engineering. A number of SBSE methods such as Simulated Annealing (SA), Genetic

Get Access