Ming-Kong Zhang

According to our database1, Ming-Kong Zhang authored at least 13 papers between 2016 and 2021.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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Links

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Bibliography

2021
Finding all Pareto optimal paths by simulating ripple relay race in multi-objective networks.
Swarm Evol. Comput., 2021

2020
Finding the k shortest paths by ripple-spreading algorithms.
Eng. Appl. Artif. Intell., 2020

2019
A benchmark test problem toolkit for multi-objective path optimization.
Swarm Evol. Comput., 2019

2018
Finding the k Shortest Paths for Co-Evolutionary Path Optimization.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2018

Finding all Pareto Optimal Paths for Dynamical Multi-Objective Path optimization Problems.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2018

2017
An approximate ripple-spreading algorithm with terminal h strategy.
Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

A ripple-spreading algorithm for calculating weighted betweenness in networks.
Proceedings of the 13th International Conference on Natural Computation, 2017

An approximate ripple-spreading algorithm to identify the k best paths.
Proceedings of the 13th International Conference on Natural Computation, 2017

2016
A ripple-spreading algorithm for network performance assessment.
Proceedings of the 2016 IEEE Symposium Series on Computational Intelligence, 2016

A new path optimization method in dynamic adverse weathers.
Proceedings of the 12th International Conference on Natural Computation, 2016

A ripple-spreading algorithm to calculate the k shortest paths in a network with time-windows.
Proceedings of the 12th International Conference on Natural Computation, 2016

An effective method to find the k shortest paths in a generalized time-window network.
Proceedings of the IEEE Congress on Evolutionary Computation, 2016

Improving the computational efficiency of ripple-spreading algorithm for the k shortest paths problem.
Proceedings of the IEEE Congress on Evolutionary Computation, 2016


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