Abstract
Constrained algorithms for BED model (Biological Effective Dose) in Head and Neck tumors HyperfractionatedTPO optimized with Pareto-Multiobjective (PMO) Genetic Algorithms (GA) software are obtained. The mathematical method for constrained GA is applied for a number of series of Pareto Functions. Results demonstrate PMO-AI imaging process sequences and extensive numerical values of PMO Head and Neck cancer parameters. Comparison and review with simple constrained GA Optimization is presented. Improved RT Head and Neck cancer TPO, and tumors in general for Fractional-dose photon dose delivery are explained in brief.
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