Genetic Algorithms for Multiobjective Optimization: FormulationDiscussion and Generalization
Proceedings of the 5th International Conference on Genetic Algorithms
Solving Multiobjective Optimization Problems Using an Artificial Immune System
Genetic Programming and Evolvable Machines
Comparison of Multiobjective Evolutionary Algorithms: Empirical Results
Evolutionary Computation
Multiobjective immune algorithm with nondominated neighbor-based selection
Evolutionary Computation
The measure of Pareto optima applications to multi-objective metaheuristics
EMO'03 Proceedings of the 2nd international conference on Evolutionary multi-criterion optimization
Quantifying the effects of objective space dimension in evolutionary multiobjective optimization
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
Overview of artificial immune systems for multi-objective optimization
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
A Survey of artificial immune applications
Artificial Intelligence Review
Hype: An algorithm for fast hypervolume-based many-objective optimization
Evolutionary Computation
On sequential online archiving of objective vectors
EMO'11 Proceedings of the 6th international conference on Evolutionary multi-criterion optimization
Omni-aiNet: an immune-inspired approach for omni optimization
ICARIS'06 Proceedings of the 5th international conference on Artificial Immune Systems
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
Multiobjective optimization by a modified artificial immune system algorithm
ICARIS'05 Proceedings of the 4th international conference on Artificial Immune Systems
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
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This paper presents a new artificial immune system algorithm for solving multi-objective optimization problems, based on the clonal selection principle and the hypervolume contribution. The main aim of this work is to investigate the performance of this class of algorithm with respect to approaches which are representative of the state-of-the-art in multi-objective optimization using metaheuristics. The results obtained by our proposed approach, called multi-objective artificial immune system based on hypervolume (MOAIS-HV) are compared with respect to those of the NSGA-II. Our preliminary results indicate that our proposed approach is very competitive, and can be a viable choice for solving multi-objective optimization problems.