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Research on Intelligent Solution of Service Industry Supply Chain Network Optimization Based on Genetic Algorithm
Author(s) -
Yixin Zhou,
Zhen Guo
Publication year - 2021
Publication title -
journal of healthcare engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.509
H-Index - 29
eISSN - 2040-2309
pISSN - 2040-2295
DOI - 10.1155/2021/9429872
Subject(s) - genetic algorithm , service (business) , personalization , computer science , supply chain , tertiary sector of the economy , task (project management) , operations research , engineering , business , marketing , systems engineering , machine learning , world wide web
With the advent of the era of big data (BD), people”s living standards and lifestyle have been greatly changed, and people's requirements for the service level of the service industry are becoming higher and higher. The personalized needs of customers and private customization have become the hot issues of current research. The service industry is the core enterprise of the service industry. Optimizing the service industry supply network and reasonably allocating the tasks are the focus of the research at home and abroad. Under the background of BD, this paper takes the optimization of service industry supply network as the research object and studies the task allocation optimization of service industry supply network based on the analysis of customers' personalized demand and user behavior. This paper optimizes the supply chain network of service industry based on genetic algorithm (GA), designs genetic operator, effectively avoids the premature of the algorithm, and improves the operation efficiency of the algorithm. The experimental results show that when m  = 8 and n  = 40, the average running time of the improved GA is 54.1 s. The network optimization running time of the algorithm used in this paper is very fast, and the stability is also higher.

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