{"title":"Effectiveness of Mixed Fuzzy Time Window Multi-objective Allocation in E-Commerce Logistics Distribution Path","authors":"Juanjuan Peng","doi":"10.1007/s44196-023-00338-y","DOIUrl":null,"url":null,"abstract":"Abstract The study of logistics distribution network under e-commerce environment is conducive to the establishment of efficient logistics distribution system, but also to promote the further development of e-commerce and improve social benefits of great significance. This study considers multiple fuzzy factors and introduces a customer fuzzy time window with variable coefficients, establishes a multi-objective set allocation integrated multi-level location path planning model, and proposes an archive type multi-objective simulated annealing improvement algorithm based on master–slave parallel framework embedded taboo search to solve the model. Tabu search and large-scale neighborhood algorithm are used to solve the initial solutions of the first level network and the second level network respectively, and archival reception criterion is introduced to deal with the multi-objective problem. The results of the proposed algorithm for the two-level site-routing problem are less than 6% different from the internationally known optimal solution. The master–slave parallel computing framework improves the efficiency of the algorithm by about 6.38%. The experimental results prove the effectiveness and necessity of the improved optimization. In addition, this study simulates the site-routing problem model constructed by the study by extending the data of standard examples. The experimental results prove the correctness and reference significance of the multilevel site-routing problem model with multiple fuzzy factors.","PeriodicalId":54967,"journal":{"name":"International Journal of Computational Intelligence Systems","volume":"51 1","pages":"0"},"PeriodicalIF":2.9000,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computational Intelligence Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s44196-023-00338-y","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract The study of logistics distribution network under e-commerce environment is conducive to the establishment of efficient logistics distribution system, but also to promote the further development of e-commerce and improve social benefits of great significance. This study considers multiple fuzzy factors and introduces a customer fuzzy time window with variable coefficients, establishes a multi-objective set allocation integrated multi-level location path planning model, and proposes an archive type multi-objective simulated annealing improvement algorithm based on master–slave parallel framework embedded taboo search to solve the model. Tabu search and large-scale neighborhood algorithm are used to solve the initial solutions of the first level network and the second level network respectively, and archival reception criterion is introduced to deal with the multi-objective problem. The results of the proposed algorithm for the two-level site-routing problem are less than 6% different from the internationally known optimal solution. The master–slave parallel computing framework improves the efficiency of the algorithm by about 6.38%. The experimental results prove the effectiveness and necessity of the improved optimization. In addition, this study simulates the site-routing problem model constructed by the study by extending the data of standard examples. The experimental results prove the correctness and reference significance of the multilevel site-routing problem model with multiple fuzzy factors.
期刊介绍:
The International Journal of Computational Intelligence Systems publishes original research on all aspects of applied computational intelligence, especially targeting papers demonstrating the use of techniques and methods originating from computational intelligence theory. The core theories of computational intelligence are fuzzy logic, neural networks, evolutionary computation and probabilistic reasoning. The journal publishes only articles related to the use of computational intelligence and broadly covers the following topics:
-Autonomous reasoning-
Bio-informatics-
Cloud computing-
Condition monitoring-
Data science-
Data mining-
Data visualization-
Decision support systems-
Fault diagnosis-
Intelligent information retrieval-
Human-machine interaction and interfaces-
Image processing-
Internet and networks-
Noise analysis-
Pattern recognition-
Prediction systems-
Power (nuclear) safety systems-
Process and system control-
Real-time systems-
Risk analysis and safety-related issues-
Robotics-
Signal and image processing-
IoT and smart environments-
Systems integration-
System control-
System modelling and optimization-
Telecommunications-
Time series prediction-
Warning systems-
Virtual reality-
Web intelligence-
Deep learning