Self-organization via competition, cooperation and categorization applied to extended vehicle routing problems

Competitive learning in neural networks involving cooperation and categorization is discussed. Extended vehicle routing problems in the Euclidean space are also discussed. A fixed number of vehicles with a shared depot make subtours around precategorized cities and collect demands. The minimal tour length and even loaded demands are conflicting requirements for the optimization. This situation does not appear in a simple traveling salesman problem. The self-organization method gives qualified approximate solutions without computational backtracks. Experiments were made on the USA532 set. All computations can be carried out by a conventional workstation