Abstract: | Abtract: Many of design problems in telecommunications could be treated as optimization problems that include some kind of searching among a set of potential solutions. The choice of the method depends mostly on the problem complexity. If the number of possible solutions is not too big, one could enumerate them all, evaluate their goal functions, and select the best solution(s). If the function to be optimized is done by a derivative continuous function, analytical methods could be applied. In all other cases, where the problem space is too big and analytical methods are not applicable, some sort of heuristic search for optimal solution could be applied. Genetic algorithms, could be classified as guided random search evolution algorithms that use probability to guide their search. Genetic algorithms are created by analogy with the processes in the reproduction of biological organisms. By natural selection or by forced selection in laboratories, new generations of organisms are produced. As a consequence of crossover and mutation processes on chromosomes and genes, the children could possess either better or worse features than their parents. The "better" organisms are those that have a greater chance than the "worse" ones to survive and to produce a new generation. |
