On the limited memory BFGS method for large scale optimization
Mathematical Programming: Series A and B
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Self-Adaptive Genetic Algorithms with Simulated Binary Crossover
Evolutionary Computation
Approximating the Nondominated Front Using the Pareto Archived Evolution Strategy
Evolutionary Computation
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
Evolutionary approach to inverse planning in coplanar radiotherapy
Image and Vision Computing
Proceedings of the 9th annual conference on Genetic and evolutionary computation
A novel case based reasoning approach to radiotherapy planning
Expert Systems with Applications: An International Journal
Evolutionary approach to inverse planning in coplanar radiotherapy
WILF'03 Proceedings of the 5th international conference on Fuzzy Logic and Applications
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We apply the NSGA-II algorithm and its controlled elitist version NSGA-IIc for the intensity modulated beam radiotherapy dose optimization problem. We compare the performance of the algorithms with objectives for which deterministic optimization methods provide global optimal solutions. The number of parameters to be optimized can be up to a few thousands and the number of objectives varies from 3 to 6. We compare the results with and without supporting solutions. Optimization with constraints for the target dose variance value provides clinical acceptable solutions.