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A Similarity Hybrid Harmony Search Algorithm for the Orienteering Problem

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Operational Research in Agriculture and Tourism

Part of the book series: Cooperative Management ((COMA))

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Abstract

In the last few years there is a continuous growth in modeling and solving of problems of different fields (logistics, tourism, games) as Orienteering Problems (OPs). The Orienteering Problem is a combinatorial optimization problem where a standard amount of nodes are given, each with a specific score. The main goal is to find a path, limited in length, from the start point to the end point through a subset of locations in order to maximize the total path score. In this paper, we present a variant of the classic Harmony Search (HS) algorithm, the Similarity Hybrid Harmony Search (SHHS) algorithm, for the solution of the Orienteering Problem. The SHHS follows the basic steps of the standard HS with some minor changes and includes a new idea considering the similarity of the feasible routes such as the musical notes of a suitable frequency for the Harmony Memory. The algorithm was tested in a number of benchmark instances from the literature and in most of them the best known solutions were found.

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References

  • Archetti, C., Speranza, M. G., & Vigo, D. (2014). Vehicle routing problems with profits. In P. Toth & D. Vigo (Eds.), Vehicle routing: Problems, methods, and applications (MOS-SIAM Series on Optimization) (pp. 273–298). Philadelphia, PA: SIAM.

    Chapter  Google Scholar 

  • Chao, I. (1993). Algorithms and solutions to multi-level vehicle routing problems. Ph.D. Dissertation, Applied Mathematics Program, University of Maryland, College Park.

    Google Scholar 

  • Chao, I. M., Golden, B. L., & Wasil, E. (1996a). A fast and effective heuristic for the orienteering problem. European Journal of Operational Research, 88(3), 475–489.

    Article  MATH  Google Scholar 

  • Chao, I. M., Golden, B. L., & Wasil, E. (1996b). The team orienteering problem. European Journal of Operational Research, 88(3), 464–474.

    Article  MATH  Google Scholar 

  • Erdal, F., Dogan, E., & Saka, M. P. (2011). Optimum design of cellular beams using harmony search and particle swarm optimizers. Journal of Constructional Steel Research, 67(2), 237–247.

    Article  Google Scholar 

  • Fourie, J., Mills, S., & Green, R. (2010). Harmony filter: A robust visual tracking system using the improved harmony search algorithm. Image and Vision Computing, 28(12), 1702–1716.

    Article  Google Scholar 

  • Geem, Z. W. (2005). School bus routing using harmony search. In GECCO 2005. Washington, DC: ACM.

    Google Scholar 

  • Geem, Z. W., Kim, J. H., & Loganathan, G. V. (2001). A new heuristic optimization algorithm: Harmony search. Simulation, 76(2), 60–68.

    Article  Google Scholar 

  • Geem, Z. W., Tseng, C.-L., & Park, Y. (2005). Harmony search for generalized orienteering problem: Best touring in China. In L. Wang, K. Chen, & Y. Ong (Eds.), ICNC 2005, LNCS 3612 (pp. 741–750). Berlin: Springer.

    Google Scholar 

  • Golden, B., Levy, L., & Vohra, R. (1987). The orienteering problem. Naval Research Logistics, 34, 307–318.

    Article  MATH  Google Scholar 

  • Kaveh, A., & Talataha, S. (2009). Particle swarm optimizer, ant colony strategy and harmony search scheme hybridized for optimization of truss structures. Computers and Structures, 87(5–6), 267–283.

    Article  Google Scholar 

  • Lee, K. S., & Geem, Z. W. (2004). A new meta-heuristic algorithm for continuous engineering optimization: Harmony search theory and practice. Computer Methods in Applied Mechanics and Engineering, 194(36–38), 3902–3933.

    MATH  Google Scholar 

  • Mahdavi, M., Fesanghary, M., & Damangir, E. (2007). An improved harmony search algorithm for solving optimization problems. Applied Mathematics and Computation, 188(2), 1567–1579.

    Article  MathSciNet  MATH  Google Scholar 

  • Marinakis, Y., Politis, M., Marinaki, M., & Matsatsinis, N. (2015). A memetic-GRASP algorithm for the solution of the orienteering problem. In H. Le Thi, T. Pham Dinh, & N. Nguyen (Eds.), Modelling, computation and optimization in information systems and management sciences (pp. 105–116). Cham: Springer.

    Chapter  Google Scholar 

  • Miguel, L. F. F., & Miguel, L. F. F. (2012). Shape and size optimization of truss structures considering dynamic constraints through modern metaheuristic algorithms. Expert Systems with Applications, 39(10), 9458–9467.

    Article  Google Scholar 

  • Montemanni, R., & Gambardella, L. (2009). Ant colony system for team orienteering problems with time windows. Foundations of Computing and Decision Sciences, 34(4), 287–306.

    MATH  Google Scholar 

  • Omran, M. G. H., & Mahdavi, M. (2008). Global-best harmony search. Applied Mathematics and Computation, 198(2), 643–656.

    Article  MathSciNet  MATH  Google Scholar 

  • Pan, Q.-K., Suganthan, P. N., Liang, J. J., & Tasgetiren, M. F. (2011). A local-best harmony search algorithm with dynamic sub-harmony memories for lot-streaming flow shop scheduling problem. Expert Systems with Applications, 38(4), 3252–3259.

    Article  Google Scholar 

  • Pan, Q.-K., Suganthan, P. N., Tasgetiren, M. F., & Liang, J. J. (2010). A self-adaptive global best harmony search algorithm for continuous optimization problems. Applied Mathematics and Computation, 216(3), 830–848.

    Article  MathSciNet  MATH  Google Scholar 

  • Pichpibul, T., & Kawtummachai, R. (2013). Modified harmony search algorithm for the capacitated vehicle routing problem. In Proceedings of the International Multi Conference of Engineers and Computer Scientists (Vol. II), IMECS 2013, Hong Kong.

    Google Scholar 

  • Righini, G., & Salani, M. (2009). Decremental state space relaxation strategies and initialization heuristics for solving the orienteering problem with time windows with dynamic programming. Computers and Operations Research, 36(4), 1191–1203.

    Article  MATH  Google Scholar 

  • Ser, J. D., Matinmikko, M., Gil-Lopez, S., & Mustonen, M. (2012). Centralized and distributed spectrum channel assignment in cognitive wireless networks: A harmony search approach. Applied Soft Computing, 12(2), 921–930.

    Article  Google Scholar 

  • Taleizadeh, A. A., Niaki, S. T. A., & Barzinpour, F. (2011). Multiple-buyer multiple-vendor multi-product multi-constraint supply chain problem with stochastic demand and variable lead-time: A harmony search algorithm. Applied Mathematics and Computation, 217(22), 9234–9253.

    Article  MathSciNet  MATH  Google Scholar 

  • Tang, H., & Miller-Hooks, E. (2005). A TABU heuristic for the team orienteering problem. Computers and Industrial Engineering, 32(6), 1379–1407.

    MATH  Google Scholar 

  • Tsiligirides, T. (1984). Heuristic methods applied to orienteering. Journal of Operational Research Society, 35(9), 797–809.

    Article  Google Scholar 

  • Vansteenwegen, P., Souffriau, W., & Van Oudheusden, D. (2011). The orienteering problem: A survey. European Journal of Operational Research, 209(1), 1–10.

    Article  MathSciNet  MATH  Google Scholar 

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Correspondence to Eleftherios Tsakirakis .

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Tsakirakis, E., Marinaki, M., Marinakis, Y. (2020). A Similarity Hybrid Harmony Search Algorithm for the Orienteering Problem. In: Krassadaki, E., Baourakis, G., Zopounidis, C., Matsatsinis, N. (eds) Operational Research in Agriculture and Tourism. Cooperative Management. Springer, Cham. https://doi.org/10.1007/978-3-030-38766-2_10

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