Abstract
The Artificial Bee Colony algorithm is a modern optimization technique based on the simulation of intelligent behavior of a swarm of bees searching for food. This algorithm is one of the Swarm Intelligence (SI) algorithms that are an integral part in the field of artificial intelligence. The use of algorithms based on swarm intelligence is an emerging area in the field of optimization, widely used in solving the Vehicle Routing Problem. This paper presents the results obtained after implementing the original modified ABC algorithm of an artificial bee colony. The task of the created system is to support the planning of the optimal route leading between the selected starting point and one of the many destination points. In this experiment, the algorithm was modified by adding a new function for one of the components of the equation. For this purpose, the division of artificial bees into scout bees, active bees and watching bees was adopted. Then a second function was added for the watching bees. These bees, apart from waiting for new solutions, strive to shorten the routes that have already been remembered. As part of the observations, five different tasks were generated for two different sets of input parameters. The computational simulations provided very encouraging results. The introduced modification results in an increase in the efficiency of the algorithm and a reduction in the time needed to find the optimal route.
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References
Czerniak, J.M., Dobrosielski, W.T., Zarzycki, H., Apiecionek, Ł.: A proposal of the new owlANT method for determining the distance between terms in ontology. In: Advances in Intelligent Systems and Computing, pp. 235–246 (2015)
Czerniak, J.M., Apiecionek, Ł., Zarzycki, H.: Application of ordered fuzzy numbers in a new OFNAnt algorithm based on Ant Colony Optimization. Commun. Comput. Inform. Sci. 424, 259–270 (2014)
Czerniak, J.M., Zarzycki, H., Ewald, D.: Application of OFN numbers in the Artificial Duroc Pigs Optimization (ADPO) method. In: Advances in Intelligent Systems and Computing (2020)
Dobrosielski, W.T., Czerniak, J.M., Szczepański, J., Zarzycki, H.: Triangular expanding, a new defuzzification method on ordered fuzzy numbers. Adv. Intell. Syst. Comput. 642, 605–619 (2017)
Engelbrecht, A.P.: Fundamentals of Computational Swarm Intelligence, John Wiley & Sons, Inc. New Jersey (2005)
Ewald, D., Czerniak, J.M., Zarzycki, H.: OFNBee method used for solving a set of benchmarks. In: Kacprzyk, J., Szmidt, E., Zadrożny, S., Atanassov, K.T., Krawczak, M. (eds.) IWIFSGN/EUSFLAT -2017. AISC, vol. 642, pp. 24–35. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-66824-6_3
Ewald, D., Zarzycki, H., Apiecionek, Ł, Czerniak, J.M.: Ordered fuzzy numbers applied in Bee swarm optimization systems. J. Univ. Comput. Sci. 26(11), 1475–1494 (2020)
Karaboga, D.: An Idea Based on Honey Bee Swarm for Numerical Optimization. Technical Report for Erciyes University, Kayseri, Turkey (2005)
Karaboga, D., Basturk, B.: A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm. J. Glob. Optim. 39, 459–471 (2007)
Karaboga, D., Basturk, B.: On the performance of artificial bee colony (ABC) algorithm. Appl. Soft Comput. 8, 687–697 (2008)
Komosiński, M.: Sztuczne życieAlgorytmy inspirowane biologicznie. Nauka 4, 7–21 (2008)
Laporte, G., Nobert, Y.: Exact algorithms for the vehicle routing problem. Ann. Discrete Math. 31, 147–184 (1987)
Merkle, D.: Swarm Intelligence: Introduction and Application, Springer Verlag (2008)
Piechowiak, M., Zwierzykowski, P.: The evaluation of multicast routing algorithms with delay constraints in mesh network. In: 8th IEEE, IET International Symposium on Communication Systems, Networks and Digital Signal Processing CSNSDP 2012, Poznań, Poland (2012)
Rozek, P.: The Application of Selected Biologically Inspired Algorithms to Solve Optimization Problems. WSIZ, Wroclaw (2021)
Toth, P., Vigo, D.: The Vehicle Routing Problem. SIAM, Thailand (2002)
Zarzycki, H., Czerniak, J.M., Dobrosielski, W.T.: Detecting nasdaq composite index trends with OFNs. In: Prokopowicz, P., Czerniak, J., Mikołajewski, D., Apiecionek, Ł, Ślȩzak, D. (eds.) Theory and Applications of Ordered Fuzzy Numbers. SFSC, vol. 356, pp. 195–205. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-59614-3_11
Zarzycki, H., Dobrosielski, W.T.: Use of ordered fuzzy numbers to observe quotations on financial markets. In: Advances in Intelligent Systems and Computing, Springer, Cham (2021)
Zarzycki, H., Dobrosielski, W.T., Vince, T., Apiecionek, Ł.: Center of circles intersection, a new defuzzification method on fuzzy numbers. Bulletin of the Polish Academy of Sciences. Technical Sciences (2020)
Zarzycki, H., Ewald, D., Skubisz, O., Kardasz, P.: A comparative study of two nature-inspired algorithms for routing optimization. In: Advances in Intelligent Systems and Computing, Springer (2021)
ABC algorithm example. https://github.com/mhmoodlan/ABC-Artificial-Bee-Colony. Accessed 11 Feb 2021
https://docs.microsoft.com/pl-pl/visualstudio/windows. Accessed 11 Feb 2021
https://docs.microsoft.com/pl-pl/dotnet/csharp. Accessed 11 Feb 2021
https://docs.microsoft.com/pl-pl/dotnet/desktop/winforms. Accessed 11 Feb 2021
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Zarzycki, H., Skubisz, O. (2022). A New Artificial Bee Colony Algorithm Approach for the Vehicle Routing Problem. In: Kahraman, C., Cebi, S., Cevik Onar, S., Oztaysi, B., Tolga, A.C., Sari, I.U. (eds) Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation. INFUS 2021. Lecture Notes in Networks and Systems, vol 307. Springer, Cham. https://doi.org/10.1007/978-3-030-85626-7_66
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