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This paper addresses several algorithms based on self‐organizing neural network approach for routing problems. The algorithm for Traveling Salesman Problem is elaborated and the extension of the proposed algorithm to more complex problems namely, Multiple Traveling Salesmen and Vehicle Routing is discussed. In order to investigate the performance of the algorithms, a comprehensive empirical study has been provided. The simulations, which are conducted on standard data, evaluate the overall performance of this approach by comparing the results with the best known or the optimal solutions of the problems. The proposed algorithm shows significant advances in both qualities of the solution and computational efforts for most of the experimented data.

This paper presents an improvement of heuristic placement algorithm for solving two-dimensional knapsack packing problem. The packing patterns were enhanced by modifying the packing rules. This approach can increase the feasibility for packing more suitable items to a container while also preserves the advantages of rules greediness. The total average percentage of trim loss is reduced nearly 15 percent in comparison with the original algorithm on 211 instances from 9 benchmark datasets.