Multiconstrained network intensive vehicle routing adaptive ant colony algorithm in the context of neural network analysis

DOI10.1155/2017/8594792zbMath1373.93045OpenAlexW2756205897MaRDI QIDQ1674845

Ji Yang, Shaopei Chen, Jingfeng Yang, Yong Li

Publication date: 26 October 2017

Published in: Complexity (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2017/8594792

zbMATH Keywords

neural networkglobal optimal solutionlocal optimal solutioncomplex traffic network systemslarge-scale multiconstrained vehicle routingpheromone adaptive strategyvehicle routing adaptive ant colony algorithm

Mathematics Subject Classification ID

Approximation methods and heuristics in mathematical programming (90C59) Neural networks for/in biological studies, artificial life and related topics (92B20) Traffic problems in operations research (90B20) Large-scale systems (93A15)

Related Items (1)

Evolutionary hyperheuristics for location-routing problem with simultaneous pickup and delivery

Cites Work

• Unnamed Item
• An improved multi-objective evolutionary algorithm for the vehicle routing problem with time windows
• A parallel algorithm for the vehicle routing problem with time window constraints
• Vibration control and boundary tension constraint of an axially moving string system
• Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem
• Modelling and control for a class of axially moving nonuniform system
• Survey Paper—Time Window Constrained Routing and Scheduling Problems
• Boundary Control for a Vibrating String System with Bounded Input

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