A study of permutation crossover operators on the traveling salesman problem
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Constructing minimum-energy broadcast trees in wireless ad hoc networks
Proceedings of the 3rd ACM international symposium on Mobile ad hoc networking & computing
Minimum-energy broadcast in all-wireless networks: NP-completeness and distribution issues
Proceedings of the 8th annual international conference on Mobile computing and networking
On the Complexity of Computing Minimum Energy Consumption Broadcast Subgraphs
STACS '01 Proceedings of the 18th Annual Symposium on Theoretical Aspects of Computer Science
Iterated Local Optimization for Minimum Energy Broadcast
WIOPT '05 Proceedings of the Third International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks
Improved heuristics for the bounded-diameter minimum spanning tree problem
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Energy-aware multicasting in wireless ad hoc networks: A survey and discussion
Computer Communications
On the performance of artificial bee colony (ABC) algorithm
Applied Soft Computing
Solving Minimum Power Broadcast Problem in Wireless Ad-Hoc Networks Using Genetic Algorithm
CNSR '08 Proceedings of the Communication Networks and Services Research Conference
An artificial bee colony algorithm for the leaf-constrained minimum spanning tree problem
Applied Soft Computing
Nested Partitioning for the Minimum Energy Broadcast Problem
Learning and Intelligent Optimization
Evolutionary local search for the minimum energy broadcast problem
EvoCOP'08 Proceedings of the 8th European conference on Evolutionary computation in combinatorial optimization
Energy concerns in wireless networks
IEEE Wireless Communications
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Given a wireless ad hoc network with a specified source node that has to broadcast messages to all other nodes in the network, the minimum energy broadcast (MEB) problem seeks a broadcast scheme for this network with minimum energy consumption. The MEB problem is NP-Hard. This paper describes a hybrid approach to the MEB problem combining a genetic algorithm with a local search heuristic. We have compared our hybrid approach against the best heuristic approaches known for this problem. Our approach outperformed all these approaches and emerged as the best.