Proceedings of the third international conference on Genetic algorithms
Data networks (2nd ed.)
Multipoint communication by hierarchically encoded data
IEEE INFOCOM '92 Proceedings of the eleventh annual joint conference of the IEEE computer and communications societies on One world through communications (Vol. 3)
SIGCOMM '93 Conference proceedings on Communications architectures, protocols and applications
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
The design and analysis of a computational model of cooperative coevolution
The design and analysis of a computational model of cooperative coevolution
Optimization flow control—I: basic algorithm and convergence
IEEE/ACM Transactions on Networking (TON)
Multicast communication: protocols and applications
Multicast communication: protocols and applications
Optimal partition of QoS requirements on unicast paths and multicast trees
IEEE/ACM Transactions on Networking (TON)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Developing IP Multicast Networks
Developing IP Multicast Networks
On Finding Feasible Solutions for the Delay Constrained Group Multicast Routing Problem
IEEE Transactions on Computers
New methods for competitive coevolution
Evolutionary Computation
Forming neural networks through efficient and adaptive coevolution
Evolutionary Computation
Research: A group multicast routing algorithm by using multiple minimum Steiner trees
Computer Communications
A framework for routing and congestion control for multicast information flows
IEEE Transactions on Information Theory
Multicast server selection: problems, complexity, and solutions
IEEE Journal on Selected Areas in Communications
A scalable low-overhead rate control algorithm for multirate multicast sessions
IEEE Journal on Selected Areas in Communications
Computing single source shortest paths using single-objective fitness
Proceedings of the tenth ACM SIGEVO workshop on Foundations of genetic algorithms
Edge-based representation beats vertex-based representation in shortest path problems
Proceedings of the 12th annual conference on Genetic and evolutionary computation
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In multirate multicasting, different users (receivers) in the same multicast group can receive service at different rates, depending on the user requirements and the network congestion level. Compared with unirate multicasting, this provides more flexibility to the users and allows more efficient usage of the network resources. In this paper, we simultaneously address the route selection and rate allocation problem in multirate multicast networks; that is, the problem of constructing multiple multicast trees and simultaneously allocating the rate of receivers for maximizing the sum of utilities over all receivers, subject to link capacity and delay constraints for high-bandwidth delay-sensitive applications in point-to-point communication networks. We propose a genetic algorithm for this problem and elaborate on many of the elements in order to improve solution quality and computational efficiency in applying the proposed methods to the problem. These include the genetic representation, evaluation function, genetic operators, and procedure. Additionally, a new method using an artificial intelligent search technique, called the coevolutionary algorithm, is proposed to achieve better solutions, and methods of selecting environmental individuals and evaluating fitness are developed. The results of extensive computational simulations show that the proposed algorithms provide high-quality solutions and outperform existing approach.