Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Evolutionary Algorithms for Solving Multi-Objective Problems
Evolutionary Algorithms for Solving Multi-Objective Problems
Artificial Immune Systems: A New Computational Intelligence Paradigm
Artificial Immune Systems: A New Computational Intelligence Paradigm
Solving Multiobjective Optimization Problems Using an Artificial Immune System
Genetic Programming and Evolvable Machines
Multiobjective Evolutionary Algorithms and Applications (Advanced Information and Knowledge Processing)
Approximating the Nondominated Front Using the Pareto Archived Evolution Strategy
Evolutionary Computation
Multiobjective optimization using ideas from the clonal selection principle
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
An novel artificial immune systems multi-objective optimization algorithm for 0/1 knapsack problems
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
Immune multiobjective optimization algorithm for unsupervised feature selection
EuroGP'06 Proceedings of the 2006 international conference on Applications of Evolutionary Computing
Clonal selection with immune dominance and anergy based multiobjective optimization
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
IFMOA: immune forgetting multiobjective optimization algorithm
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part III
EC'05 Proceedings of the 3rd European conference on Applications of Evolutionary Computing
Handling constraints in global optimization using an artificial immune system
ICARIS'05 Proceedings of the 4th international conference on Artificial Immune Systems
Multiobjective optimization by a modified artificial immune system algorithm
ICARIS'05 Proceedings of the 4th international conference on Artificial Immune Systems
Evolutionary multi-objective optimization: a historical view of the field
IEEE Computational Intelligence Magazine
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Learning and optimization using the clonal selection principle
IEEE Transactions on Evolutionary Computation
Cost-effective base station deployment approach based on artificial immune systems
Proceedings of the 3rd International Conference on Bio-Inspired Models of Network, Information and Computing Sytems
A multi-objective artificial immune system based on hypervolume
ICARIS'12 Proceedings of the 11th international conference on Artificial Immune Systems
ICARIS'12 Proceedings of the 11th international conference on Artificial Immune Systems
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Evolutionary algorithms have become a very popular approach for multiobjective optimization in many fields of engineering. Due to the outstanding performance of such techniques, new approaches are constantly been developed and tested to improve convergence, tackle new problems, and reduce computational cost. Recently, a new class of algorithms, based on ideas from the immune system, have begun to emerge as problem solvers in the evolutionary multiobjective optimization field. Although all these immune algorithms present unique, individual characteristics, there are some trends and common characteristics that, if explored, can lead to a better understanding of the mechanisms governing the behavior of these techniques. In this paper we propose a common framework for the description and analysis of multiobjective immune algorithms.