Abstract
This paper concentrates on the created algorithm for solving the single machine total weighted tardiness problem (SMTWT). The algorithm is based on searching the solution space along with the tree rules. The properties of the algorithm are studied taking into account the results of experiments made using the designed and implemented experimentation system. This system allows testing various configurations of the algorithm as well as comparing the effects obtained by this algorithm with effects of known meta-heuristic algorithms, which are based on Simulated Annealing and Invasive Weed Optimization. The paper shows that the proposed algorithm requires some improvements, however seems to be promising.
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This work was supported by the statutory funds of the Department of Systems and Computer Networks, Wroclaw University of Science and Technology, Wroclaw, Poland, grant No. 0401/0154/17.
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Petrynski, K., Szost, R., Pozniak-Koszalka, I., Koszalka, L., Kasprzak, A. (2018). Single Machine Weighted Tardiness Problem: An Algorithm and Experimentation System. In: Nguyen, N., Pimenidis, E., Khan, Z., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2018. Lecture Notes in Computer Science(), vol 11056. Springer, Cham. https://doi.org/10.1007/978-3-319-98446-9_4
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DOI: https://doi.org/10.1007/978-3-319-98446-9_4
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