Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Lifetime aware resource management for sensor network using distributed genetic algorithm
Proceedings of the 2006 international symposium on Low power electronics and design
Mobile-C: a mobile agent platform for mobile C-C++ agents
Software—Practice & Experience
Multi-sensor fusion: an Evolutionary algorithm approach
Information Fusion
Adaptive design optimization of wireless sensor networks using genetic algorithms
Computer Networks: The International Journal of Computer and Telecommunications Networking
Analysis of the publications on the applications of particle swarm optimisation
Journal of Artificial Evolution and Applications - Regular issue
XML-based agent communication, migration and computation in mobile agent systems
Journal of Systems and Software
Artificial immune pattern recognition for structure damage classification
Computers and Structures
Agent-based artificial immune system approach for adaptive damage detection in monitoring networks
Journal of Network and Computer Applications
An analytical model for predicting the remaining battery capacity of lithium-ion batteries
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Editorial: Control and optimization over wireless networks
Journal of Network and Computer Applications
Free Search with Adaptive Differential Evolution Exploitation and Quantum-Inspired Exploration
Journal of Network and Computer Applications
User-centric infrastructure as a service by Cloud Agency
Multiagent and Grid Systems
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This paper studies optimal control of mobile monitoring agents in artificial-immune-system-based (AIS-based) monitoring networks. In AIS-based structural health monitoring (SHM) networks, the active structural health monitoring is performed by a group of mobile monitoring agents equipped with damage pattern recognition algorithms. The mobile monitoring agents mimic immune cells in the natural immune system and patrol a structure to detect damage patterns using their receptors (feature vectors), damage pattern recognition algorithms, and the dynamic response data of the structure. The optimal control of mobile monitoring agents includes agent generation and distribution. The generation of mobile monitoring agents is optimized to minimize the response time for the mobile monitoring agents to diagnose structural damage in a sub-network and maximize the average affinity of monitoring agents' receptors to the damaged sensor data feature vector. The objective functions for distributing mobile monitoring agents are to increase the detection probability and extend network life by balancing energy consumption of sensor nodes in the network. The presented optimization algorithms are developed using multi-objective genetic algorithms. The impact of the algorithm parameters on the performance of the algorithm is also investigated.