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A Multi-Directional Modified Physarum Algorithm for Optimal Multi-Objective Discrete Decision Making

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EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation III

Part of the book series: Studies in Computational Intelligence ((SCI,volume 500))

Abstract

This paper will address an innovative bio-inspired algorithm able to incrementally grow decision graphs in multiple directions for discrete multi-objective optimisation. The algorithm takes inspiration from the slime mould Physarum Polycephalum, an amoeboid organism that in its plasmodium state extends and optimizes a net of veins looking for food. The algorithm is here used to solve multi-objective Traveling Salesman and Vehicle Routing Problems selected as representative examples of multi-objective discrete decision making problems. Simulations on selected test cases showed that building decision sequences in two directions and adding a matching ability (multi-directional approach) is an advantageous choice if compared with the choice of building decision sequences in only one direction (unidirectional approach). The ability to evaluate decisions from multiple directions enhances the performance of the solver in the construction and selection of optimal decision sequences.

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References

  1. Dorigo, M., Maniezzo, V., Colorni, A.: The Ant System: optimisation by a colony of cooperating agents. IEEE Transactions on Systems, Man, and Cybernetics-Part B 26(1), 29–41 (1996)

    Article  Google Scholar 

  2. Chong, C.S., Low, M.Y.H., Sivakumar, A.I., Gay, K.L.: A bee colony optimisation algorithm to job shop scheduling. In: Proceedings of the Winter IEEE Simulation Conference, WSC 2006, pp. 1954–1961 (2006)

    Google Scholar 

  3. Sayadi, M.K., Ramezanian, R., Ghaffari-Nasab, N.: A discrete firefly meta-heuristic with local search for makespan minimisation in permutation flow shop scheduling problems. International Journal of Industrial Engineering Computations 1(1), 1–10 (2010)

    Article  Google Scholar 

  4. Yang, X.-S., Deb, S.: Cuckoo search via Levy flights. In: World Congress on Nature & Biologically Inspired Computing, NaBIC 2009, pp. 210–214. IEEE (2009)

    Google Scholar 

  5. Nakagaki, T., Yamada, H., Toth, A.: Maze-Solving by an Amoeboid Organism. Nature 407, 470 (2000)

    Article  Google Scholar 

  6. Tero, A., Takagi, S., Saigusa, T., Ito, K., Bebber, D.P., Fricker, M.D., Yumiki, K., Kobayashi, R., Nakagaki, T.: Rules for Biologically Inspired Adaptive Network Design. Science 439, 327 (2010)

    MathSciNet  Google Scholar 

  7. Adamatzky, A., Martínez, G.J., Chapa-Vergara, S.V., Asomoza-Palacio, R., Stephens, C.R.: Approximating Mexican highways with slime mould. Natural Computing 10(3), 1195–1214 (2011)

    Article  MathSciNet  Google Scholar 

  8. Hickey, D.S., Noriega, L.A.: Insights into Information Processing by the Single Cell Slime Mold Physarum Polycephalum. In: UKACC Control Conference (2008)

    Google Scholar 

  9. Tero, A., Yumiki, K., Kobayashi, R., Saigusa, T., Nakagaki, T.: Flow-Network Adaptation in Physarum Amoebae. Theory in Biosciences 127(2), 89–94 (2008)

    Article  Google Scholar 

  10. Tero, A., Kobayashi, R., Nakagaki, T.: Physarum Solver: a Biologically Inspired Method of Road-Network Navigation. Physica: A Statistical Mechanics and its Applications 363(1), 115–119 (2006)

    Article  Google Scholar 

  11. Alaya, I., Solnon, C., Ghedira, K.: Ant colony optimisation for multi-objective optimisation problems. In: 19th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2007, vol. 1, pp. 450–457 (2007)

    Google Scholar 

  12. Lopez-Ibanez, M.: Multi-objective Ant Colony optimisation. Diploma thesis, Intellectics Group, Computer Science Department, Technische Universitat Darmstadt, Germany (2004)

    Google Scholar 

  13. Garcia-Martinez, C., Cordon, O., Herrera, F.: A Taxonomy and an Empirical Analysis of Multiple Objective Ant Colony optimisation Algorithms for the Bi-Criteria TSP. European Journal of Operational Research 180, 116–148 (2007)

    Article  MATH  Google Scholar 

  14. Masi, L., Vasile, M.: A multi-directional Modified Physarum Solver for Optimal Discrete Decision Making. In: Proceedings of International Conference on Bio-Inspired Optimisation Methods and their Applications, BIOMA, Bohinj, Slovenia (2012)

    Google Scholar 

  15. Dorigo, M., Gambardella, L.M.: Ant Colonies for the Traveling Salesman Problem. BioSystems 43, 73–81 (1997)

    Article  Google Scholar 

  16. Monismith Jr., D.R., Mayfield, B.E.: Slime Mold as a Model for Numerical optimisation. In: IEEE Swarm Intelligence Symposium, St. Louis MO, USA (2008)

    Google Scholar 

  17. TSPLIB, library of instances for Traveling Salesman and Vehicle Routing Problems, Ruprecht Karls Universitaet Heidelberg, http://comopt.ifi.uni-heidelberg.de/software/TSPLIB95/

  18. Vasile, M., Zuiani, F.: MACS: An Agent-Based Memetic Multiobjective optimisation Algorithm Applied to Space Trajectory Design. Journal of Aerospace Engineering, Institution of Mechanical Engineers, Part G (September 2011)

    Google Scholar 

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Masi, L., Vasile, M. (2014). A Multi-Directional Modified Physarum Algorithm for Optimal Multi-Objective Discrete Decision Making. In: Schuetze, O., et al. EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation III. Studies in Computational Intelligence, vol 500. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-01460-9_9

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  • DOI: https://doi.org/10.1007/978-3-319-01460-9_9

  • Publisher Name: Springer, Heidelberg

  • Print ISBN: 978-3-319-01459-3

  • Online ISBN: 978-3-319-01460-9

  • eBook Packages: EngineeringEngineering (R0)

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