Scheduling algorithms for multihop radio networks
IEEE/ACM Transactions on Networking (TON)
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
An optimal topology-transparent scheduling method in multihop packet radio networks
IEEE/ACM Transactions on Networking (TON)
Memetic algorithms: a short introduction
New ideas in optimization
Broadcast scheduling for TDMA in wireless multihop networks
Handbook of wireless networks and mobile computing
Using Genetic Algorithms to Solve NP-Complete Problems
Proceedings of the 3rd International Conference on Genetic Algorithms
Neural Networks - 2005 Special issue: IJCNN 2005
Delay-Constrained Multicast Routing Using the Noisy Chaotic Neural Networks
IEEE Transactions on Computers
An immune-genetic algorithm for introduction planning of new products
Computers and Industrial Engineering
An efficient algorithm to find broadcast schedule in ad hoc TDMA networks
Journal of Computer Systems, Networks, and Communications
A memetic algorithm applied to the design of water distribution networks
Applied Soft Computing
A sequential approach for optimal broadcast scheduling in packet radio networks
IEEE Transactions on Communications
Efficient algorithms to solve Broadcast Scheduling problem in WiMAX mesh networks
Computer Communications
IEEE Transactions on Computers
Load-balanced IP routing scheme based on shortest paths in hose model
IEEE Transactions on Communications
IEEE Transactions on Neural Networks
A mixed neural-genetic algorithm for the broadcast scheduling problem
IEEE Transactions on Wireless Communications
A novel genetic algorithm based on immunity
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A heuristic algorithm for optimum transmission schedule in broadcast packet radio networks
Computer Communications
Optimal broadcast scheduling in packet radio networks using mean field annealing
IEEE Journal on Selected Areas in Communications
IEEE Transactions on Neural Networks
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A technical challenge in successful deployment and utilization of wireless multihop networks (WMN) are to make effective use of the limited channel bandwidth. One method to solve this challenge is broadcast scheduling of channel usage by the way of time division multiple access (TDMA). Three evolutionary algorithms, namely genetic algorithm (GA), immune genetic algorithm (IGA) and memetic algorithm (MA) are used in this study to solve broadcast scheduling for TDMA in WMN. The aim is to minimize the TDMA cycle length and maximize the node transmissions with reduced computation time. In comparison to GA and IGA, MA actively aim on improving the solutions and is explicitly concerned in exploiting all available knowledge about the problem. The simulation results on numerous problem instances confirm that MA significantly outperforms several heuristic and evolutionary algorithms by solving well-known benchmark problem in terms of solution quality, which also demonstrates the effectiveness of MA in efficient use of channel bandwidth.