Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
A fast quantum mechanical algorithm for database search
STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing
Journal of Global Optimization
Journal of Global Optimization
Evolution, Sociobiology, and the Future of Artificial Intelligence
IEEE Intelligent Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Algorithms for quantum computation: discrete logarithms and factoring
SFCS '94 Proceedings of the 35th Annual Symposium on Foundations of Computer Science
ITCS '09 Proceedings of the 2009 International Conference on Information Technology and Computer Science - Volume 01
Journal of Network and Computer Applications
Free Search - A Model of Adaptive Intelligence
ICAIS '09 Proceedings of the 2009 International Conference on Adaptive and Intelligent Systems
Free search differential evolution
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Free Search-a comparative analysis
Information Sciences: an International Journal
JADE: adaptive differential evolution with optional external archive
IEEE Transactions on Evolutionary Computation
Research and Improvement of Free Search Algorithm
AICI '09 Proceedings of the 2009 International Conference on Artificial Intelligence and Computational Intelligence - Volume 01
Solving ring loading problems using bio-inspired algorithms
Journal of Network and Computer Applications
RFID network planning using a multi-swarm optimizer
Journal of Network and Computer Applications
Using bee algorithm for peer-to-peer file searching in mobile ad hoc networks
Journal of Network and Computer Applications
Optimal control of mobile monitoring agents in immune-inspired wireless monitoring networks
Journal of Network and Computer Applications
MSDP with ACO: A maximal SRLG disjoint routing algorithm based on ant colony optimization
Journal of Network and Computer Applications
Quantum-inspired evolutionary algorithm for a class of combinatorial optimization
IEEE Transactions on Evolutionary Computation
Differential Evolution: A Survey of the State-of-the-Art
IEEE Transactions on Evolutionary Computation
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Recently an interesting evolutionary mechanism, sensibility, inherited from a concept model of Free Search (FS) was introduced and used for solving network problems. Unfortunately, the original FS is not easy to implement because it requires key knowledge that is not clearly defined in the existing literature to determine the neighborhood space that profoundly affects the performance of the original FS. This paper thus designs a new implementation for the concept model of FS, and proposes a new algorithm, called Free Search with Adaptive Differential Evolution Exploitation and Quantum-Inspired Exploration (ADEQFS) to address this issue. In ADEQFS, we focus on designing a new mutation strategy by employing adaptive differential evolution techniques as well as concepts and principles from real-coded quantum-inspired evolutionary algorithm. In addition, we use the crossover operation from the traditional Differential Evolution scheme to alleviate the premature convergence for the proposed algorithm. Furthermore, we employ the greedy mechanism to preserve the best solutions found at each generation. The convergence analysis of the proposed algorithm is also presented in this paper. We give the proof of convergence by using the Markov chain model. Thirty-four optimization test functions with different mathematical characteristics are employed as benchmark set to test the performance of ADEQFS. The numerical results highlight the improved convergence rate and computation reliability.