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

Jeng-Shyang Pan (), Qing-yong Yang (), Shu-Chuan Chu () and Kuo-Chi Chang ()
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Jeng-Shyang Pan: Shandong University of Science and Technology
Qing-yong Yang: Shandong University of Science and Technology
Shu-Chuan Chu: Shandong University of Science and Technology
Kuo-Chi Chang: Fujian University of Technology

Telecommunication Systems: Modelling, Analysis, Design and Management, 2021, vol. 78, issue 4, No 9, 609-628

Abstract: 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.

Keywords: Sine Cosine Algorithm; Compact optimization; VRPTW; Intergeneration sampling (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s11235-021-00833-7

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