Research on takeaway order path optimization based on elite genetic algorithm

Chunyou Yang; Wenxiang Wu

doi:10.1117/12.3034979

7 August 2024 Research on takeaway order path optimization based on elite genetic algorithm

Chunyou Yang, Wenxiang Wu

Proceedings Volume 13224, 4th International Conference on Internet of Things and Smart City (IoTSC 2024); 132240X (2024) https://doi.org/10.1117/12.3034979
Event: 4th International Conference on Internet of Things and Smart City, 2024, Hangzhou, China

Abstract

With the rapid development of the takeaway industry, the takeaway order path optimization problem has attracted extensive attention from many scholars. However, most of the existing researches only focus on customer satisfaction, ignoring the attention of takeaway workers. Therefore, this paper carries out an in-depth study on the income status of takeout workers on the basis of previous studies. First, this paper establishes a multi-objective order path optimization model, which not only considers the time delay of the order and the cost of the rider's driving path, but also takes into account the goal of the rider's income equilibrium, and fully integrates the take-out workers, merchants and customers. Secondly, an elite genetic algorithm with repair operator is designed to solve the objective function solving problem in dynamic scenarios. The arithmetic example is analyzed by real-time data of takeaway delivery. The results show that the model and algorithm proposed in this paper can effectively solve the problem, and the algorithm performs well in terms of solving efficiency and accuracy compared with the classical genetic algorithm.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Chunyou Yang and Wenxiang Wu "Research on takeaway order path optimization based on elite genetic algorithm", Proc. SPIE 13224, 4th International Conference on Internet of Things and Smart City (IoTSC 2024), 132240X (7 August 2024); https://doi.org/10.1117/12.3034979

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available