Please, solve mathematical model. Excel is not neccessary.

Consider the radiation therapy problem where a doctor wants to minimize the total dosage of radiation delivered to the cells (where cells are represented by pixel (i, j)). The constraints are such that the dosage over the tumor area will be at least a target level (R) and that the dosage over the critical area (normal cells) will be at most a target level (R). (a) Complete the following LP. Let D-unit dose delivered to pixel (i, j) by beamlet p, R- the lower bound of dosage exposed to tumor cells, and Ruthe upper bound of the dosage exposed to normal cells. The decision variables are w-(wi, w.), where to, is the intensity weight assigned to beamlet p for p=1 to n; PU Minimize s. t. Du-- (Hint: Du-dosage delivered to pixel (i, j).) Du 2 R for (i, j) ET (tumor/cancer cells) Du S R for (i, j) E C (criticalormal cells) W, 20 for all p (b) It is far better to set the parameters (R. and R) conservatively while allowing some violation. If there is no feasible solution to the original problem, there will definitely be a for all p (b) It is far better to set the parameters (R. and R) conservatively while allowing some violation. If there is no feasible solution to the original problem, there will definitely be a feasible solution to the following nonlinear program since one can choose Y to guarantee feasibility. In the following NLP model, the objective function would try to set all of the y's to 0. Failing that, it would set all of the y's as small as possible. Complete the following NLP model. (Y4) Minimize s. t Du-. (Same as in the previous LP model) for (i, j) ET (tumor/cancer cells) for (i, j) E C (criticalormal cells) W, Y, 2 0 > R S RH for all p, for all (ij)