Lipschitzian optimization without the Lipschitz constant
Journal of Optimization Theory and Applications
Artificial Immune Systems: A New Computational Intelligence Paradigm
Artificial Immune Systems: A New Computational Intelligence Paradigm
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
Evolutionary Optimization Versus Particle Swarm Optimization: Philosophy and Performance Differences
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
Artificial Immune Systems: Third International Conference, ICARIS 2004, Catania, Sicily, Italy, September 13-16, 2004, Proceedings (Lecture Notes in Computer Science)
A hybrid immune algorithm with information gain for the graph coloring problem
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Immune inspired somatic contiguous hypermutation for function optimisation
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
EvoCOP'05 Proceedings of the 5th European conference on Evolutionary Computation in Combinatorial Optimization
Combining mutation operators in evolutionary programming
IEEE Transactions on Evolutionary Computation
Evolutionary programming made faster
IEEE Transactions on Evolutionary Computation
Learning and optimization using the clonal selection principle
IEEE Transactions on Evolutionary Computation
Proceedings of the 2006 ACM symposium on Applied computing
A distributed ant-based algorithm for numerical optimization
BADS '09 Proceedings of the 2009 workshop on Bio-inspired algorithms for distributed systems
A stigmergy-based algorithm for black-box optimization: noiseless function testbed
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
A stigmergy-based algorithm for black-box optimization: noisy function testbed
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
ICARIS '09 Proceedings of the 8th International Conference on Artificial Immune Systems
Hybrid immune algorithm for many optima
ICAISC'10 Proceedings of the 10th international conference on Artifical intelligence and soft computing: Part II
An immune-inspired approach to qualitative system identification of biological pathways
Natural Computing: an international journal
Clonal selection: an immunological algorithm for global optimization over continuous spaces
Journal of Global Optimization
ICARIS'12 Proceedings of the 11th international conference on Artificial Immune Systems
Multi-core implementation of the differential ant-stigmergy algorithm for numerical optimization
The Journal of Supercomputing
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Numerical optimization of given objective functions is a crucial task in many real-life problems. The present article introduces an immunological algorithm for continuous global optimization problems, called opt-IA. Several biologically inspired algorithms have been designed during the last few years and have shown to have very good performance on standard test bed for numerical optimization. In this paper we assess and evaluate the performance of opt-IA, FEP, IFEP, DIRECT, CEP, PSO, and EO with respect to their general applicability as numerical optimization algorithms. The experimental protocol has been performed on a suite of 23 widely used benchmarks problems. The experimental results show that opt-IA is a suitable numerical optimization technique that, in terms of accuracy, generally outperforms the other algorithms analyzed in this comparative study. The opt-IA is also shown to be able to solve large-scale problems.