Sine Cosine Algorithm with Multigroup and Multistrategy for Solving CVRP

Qingyong Yang, Shu-Chuan Chu, Jeng-Shyang Pan, Chien-Ming Chen

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40 Citations (Scopus)
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Sine Cosine Algorithm (SCA) has been proved to be superior to some existing traditional optimization algorithms owing to its unique optimization principle. However, there are still disadvantages such as low solution accuracy and poor global search ability. Aiming at the shortcomings of the sine cosine algorithm, a multigroup multistrategy SCA algorithm (MMSCA) is proposed in this paper. The algorithm executes multiple populations in parallel, and each population executes a different optimization strategy. Information is exchanged among populations through intergenerational communication. Using 19 different types of test functions, the optimization performance of the algorithm is tested. Numerical experimental results show that the performance of the MMSCA algorithm is better than that of the original SCA algorithm, and it also has some advantages over other intelligent algorithms. At last, it is applied to solving the capacitated vehicle routing problem (CVRP) in transportation. The algorithm can get better results, and the practicability and feasibility of the algorithm are also proved.
Original languageEnglish
Article number8184254
Number of pages10
Publication statusPublished - 1 Jan 2020
Externally publishedYes

Bibliographical note

Copyright © 2020 Qingyong Yang et al. ,is is an open access article distributed under the Creative Commons Attribution
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is
properly cited.


  • Sine Cosine Algorithm
  • Multigroup multistrategy SCA
  • CVRP


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