Question

Difference between genetic algorithm and traditional methods

Answer 1

Genetic Algorithms and Traditional Optimum Search Methods. This section describes the differences between genetic algorithms and traditional optimum search methods. A standard genetic algorithm deals with a set (a population) of possible solutions (individuals) of a problem.

Answer 2

The genetic algorithm is a technique for determining both restrained and unconstrained optimization queries that are based on the actual range, the process that encourages biological development. The genetic algorithm regularly transforms a population of specific solutions.

Difference between genetic algorithm and traditional methods area s follows;

GA's work with sequence coding of variables preferably of variables. So that coding discretizing the exploration space even though the function is constant.

GA's work with an association of points rather of a single point.

In GA's earlier found good data is emphasized during generation operator and developed adaptively through crossover and modification operators.

GA does not need any auxiliary data except the physical function values.

This nature of narrowing the research space as the search advances is adaptive and is the unusual feature of Genetic Algorithms.