Evolutionary Algorithms for Solving Multi-Objective Problems
Evolutionary Algorithms for Solving Multi-Objective Problems
Multiple Objective Optimization with Vector Evaluated Genetic Algorithms
Proceedings of the 1st International Conference on Genetic Algorithms
A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimisation: NSGA-II
PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
AE '95 Selected Papers from the European conference on Artificial Evolution
An analysis of the behavior of a class of genetic adaptive systems.
An analysis of the behavior of a class of genetic adaptive systems.
Multiobjective evolutionary algorithms: classifications, analyses, and new innovations
Multiobjective evolutionary algorithms: classifications, analyses, and new innovations
Comparison of Multiobjective Evolutionary Algorithms: Empirical Results
Evolutionary Computation
An overview of evolutionary algorithms in multiobjective optimization
Evolutionary Computation
Multi-objective genetic algorithms: Problem difficulties and construction of test problems
Evolutionary Computation
Evolutionary algorithms for constrained parameter optimization problems
Evolutionary Computation
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
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
The balance between proximity and diversity in multiobjective evolutionary algorithms
IEEE Transactions on Evolutionary Computation
Rank-density-based multiobjective genetic algorithm and benchmark test function study
IEEE Transactions on Evolutionary Computation
Handling multiple objectives with particle swarm optimization
IEEE Transactions on Evolutionary Computation
Application areas of AIS: The past, the present and the future
Applied Soft Computing
Multiobjective immune algorithm with nondominated neighbor-based selection
Evolutionary Computation
Overview of artificial immune systems for multi-objective optimization
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
Multi-objective immune algorithm with Baldwinian learning
Applied Soft Computing
A multi-objective artificial immune system based on hypervolume
ICARIS'12 Proceedings of the 11th international conference on Artificial Immune Systems
Clustering-Based multi-objective immune optimization evolutionary algorithm
ICARIS'12 Proceedings of the 11th international conference on Artificial Immune Systems
A preference multi-objective optimization based on adaptive rank clone and differential evolution
Natural Computing: an international journal
A novel micro-population immune multiobjective optimization algorithm
Computers and Operations Research
| Hi-index | 0.00 |
The aim of this work is to propose and validate a new multiobjective optimization algorithm based on the emulation of the immune system behavior. The rationale of this work is that the artificial immune system has, in its elementary structure, the main features required by other multiobjective evolutionary algorithms described in literature. The proposed approach is compared with the NSGA2 algorithm, that is representative of the state-of-the-art in multiobjective optimization. Algorithms are tested versus three standard problems (unconstrained and constrained), and comparisons are carried out using three different metrics. Results show that the proposed approach have performances similar or better than those produced by NSGA2, and it can become a valid alternative to standard algorithms.