Population-Based Learning Algorithm to Solving Permutation Scheduling Problems

Population-based methods are optimization techniques inspired by natural evolution processes. They handle a population of individuals that evolves with the help of information exchange procedures. Each individual may also evolve independently. Periods of cooperation alternatewith periods of self-adaptation. Population-based Learning Algorithm (PBLA), is another population-based method, which can be applied to solve combinatorial optimization problems. PBLA has been inspired by analogies to a social phenomenon rather than to evolutionary processes.Whereas evolutionary algorithms emulate basic features of natural evolution including natural selection, hereditary variations, the survival of the fittest, and production of far more offspring than are necessary to replace current generation.