Bionic search for transportation problem solution on the basis of adaptation strategy

The development of methods and algorithms for solving a routing problem is being implemented over the years, but it is still a topical problem. This is, primarily, due to the fact that this problem is NP-complete, and to develop a universal algorithm for finding an exact optimal solution during a reasonable time is difficult. In this regard, in order to reduce the algorithm time complexity (ATC), the development of sequential and parallel bionic algorithms for solving the transportation problems based on the evolutionary strategies is prospective. The bionic algorithms (BA) have proved their efficiency at the solution of the time-consuming tasks of optimization, approximation, and intellectual data processing. Benefits include the possibility to perform the genetic and evolutionary search, as well as the fact that BA consist in parallel generation of the quasioptimal alternative decision sets with possible "migration" of decisions between these sets. Schemes that differ from the known ones in the outlining structure and recording the parameter variation are proposed for the bionic search simulation. The investigation of the developed bionic algorithms for solving transportation problems show the advantage in the solution quality compared to the known methods. The developed algorithms allow obtaining a set of alternative quasioptimal results with the polynomial time complexity. The transformation of the population size during the transition from one iteration to another in the process of the bionic algorithm operation is presented.