Multiconstrained Network Intensive Vehicle Routing Adaptive Ant Colony Algorithm in the Context of Neural Network Analysis
المؤلفون المشاركون
Yang, Jingfeng
Li, Yong
Chen, Shaopei
Yang, Ji
المصدر
العدد
المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-9، 9ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2017-09-18
دولة النشر
مصر
عدد الصفحات
9
التخصصات الرئيسية
الملخص EN
Neural network models have recently made significant achievements in solving vehicle scheduling problems.
Adaptive ant colony algorithm provides a new idea for neural networks to solve complex system problems of multiconstrained network intensive vehicle routing models.
The pheromone in the path is changed by adjusting the volatile factors in the operation process adaptively.
It effectively overcomes the tendency of the traditional ant colony algorithm to fall easily into the local optimal solution and slow convergence speed to search for the global optimal solution.
The multiconstrained network intensive vehicle routing algorithm based on adaptive ant colony algorithm in this paper refers to the interaction between groups.
Adaptive transfer and pheromone update strategies are introduced based on the traditional ant colony algorithm to optimize the selection, update, and coordination mechanisms of the algorithm further.
Thus, the search task of the objective function for a feasible solution is completed by the search ants.
Through the division and collaboration of different kinds of ants, pheromone adaptive strategy is combined with polymorphic ant colony algorithm.
It can effectively overcome some disadvantages, such as premature stagnation, and has a theoretical significance to the study of large-scale multiconstrained vehicle routing problems in complex traffic network systems.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Chen, Shaopei& Yang, Ji& Li, Yong& Yang, Jingfeng. 2017. Multiconstrained Network Intensive Vehicle Routing Adaptive Ant Colony Algorithm in the Context of Neural Network Analysis. Complexity،Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1143559
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Chen, Shaopei…[et al.]. Multiconstrained Network Intensive Vehicle Routing Adaptive Ant Colony Algorithm in the Context of Neural Network Analysis. Complexity No. 2017 (2017), pp.1-9.
https://search.emarefa.net/detail/BIM-1143559
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Chen, Shaopei& Yang, Ji& Li, Yong& Yang, Jingfeng. Multiconstrained Network Intensive Vehicle Routing Adaptive Ant Colony Algorithm in the Context of Neural Network Analysis. Complexity. 2017. Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1143559
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1143559
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر