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Compact Sine Cosine Algorithm applied in vehicle routing problem with time window

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Abstract

In this paper, the compact Sine Cosine Algorithm (cSCA) is proposed. The cSCA algorithm is not based on population, but simulates the behavior of the actual population through a probability model called virtual population. Compared with the original algorithm, the cSCA algorithm takes up less memory space. However, frequent sampling may lead to poor solution quality. In view of this situation, this paper introduces the intergenerational generation sampling mechanism to improve the cSCA algorithm. Through the CEC2013 function set test, compared with the original SCA algorithm and other compact algorithms, the algorithm proposed in this paper can show strong solving ability. Finally, this paper describes how to apply the proposed algorithm and the SCA algorithm to solve the vehicle routing problem with time window in transportation. The quality of the solution is further improved by introducing the relocate operator. Through Solomon standard test data, the calculation performance of the algorithms is verified.

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Authors and Affiliations

  1. College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, 266590, China

    Jeng-Shyang Pan, Qing-yong Yang & Shu-Chuan Chu

  2. Fujian Provincial Key Laboratory of Big Data Mining and Applications, Fujian University of Technology, Fuzhou, China

    Kuo-Chi Chang

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  1. Jeng-Shyang Pan
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Appendices

Appendix A: Comparison of test results of cSCA_n, cSCA and oSCA

See Tables 2, 3, and 4.

Table 4 Comparison of 50D test results of cSCA_n, cSCA and oSCA
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Appendix B: Comparsion of test results of compact algorithms

See Tables 5 and 6.

Table 5 Comparison of other compact algorithms on 30D
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Table 6 Comparison of other compact algorithms on 50D
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Pan, JS., Yang, Qy., Chu, SC. et al. Compact Sine Cosine Algorithm applied in vehicle routing problem with time window. Telecommun Syst 78, 609–628 (2021). https://doi.org/10.1007/s11235-021-00833-7

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