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  \displaystyle \min_{x, u} & x_0(t_f) &+& \alpha \int_{t_0}^{t_f} u_0(t)^2 \text{d}t  \\[1.5ex]
  \displaystyle \min_{x, u} & x_0(t_f) &+& \alpha \int_{t_0}^{t_f} u_0(t)^2 \text{d}t  \\[1.5ex]
  \mbox{s.t.} & \dot{x}_0 & = & - \zeta x_0 \text{ln} \left( \frac{x_0}{x_1} \right) - \sum\limits_{i=1}^{4} w_i\;c_{1,i}\; F \; x_0 , \\
  \mbox{s.t.} & \dot{x}_0 & = & - \zeta x_0 \text{ln} \left( \frac{x_0}{x_1} \right) - \sum\limits_{i=1}^{4} w_i\;c_{1,i}\; F \; x_0 , \\
             & \dot{x}_1 & = & b x_0 - \mu x_1 - d x_0^{\frac{2}{3}}x_1 -\sum\limits_{i=1}^{4} w_i c_{0,i} G x_1 - \sum\limits_{i=1}^{4} w_i\;c_{1,i} \eta x_1,  \\
             & \dot{x}_1 & = & b x_0 - \mu x_1 - d x_0^{\frac{2}{3}}x_1 -\sum\limits_{i=1}^{4} w_i c_{0,i} \; G x_1 - \sum\limits_{i=1}^{4} w_i\;c_{1,i} \; \eta x_1,  \\
             & \dot{x}_2 & = & \sum\limits_{i=1}^{4} w_i\;c_{0,i},  \\
             & \dot{x}_2 & = & \sum\limits_{i=1}^{4} w_i\;c_{0,i},  \\
             & \dot{x}_3 & = & \sum\limits_{i=1}^{4} w_i\;c_{1,i}, \\ [1.5ex]
             & \dot{x}_3 & = & \sum\limits_{i=1}^{4} w_i\;c_{1,i}, \\ [1.5ex]
             & x_2 & \leq & x_2^{max},  \\
             & x_2 & \leq & x_2^{max},  \\
             & x_3 & \leq & x_3^{max},\\
             & x_3 & \leq & x_3^{max},\\
& 1 &=& \sum\limits_{i=1}^{3}w_i(t), \\
& 1 &=& \sum\limits_{i=1}^{4}w_i(t), \\
  & w_i(t) &\in&  \{0, 1\}, \quad i=1\ldots 4.
  & w_i(t) &\in&  \{0, 1\}, \quad i=1\ldots 4.
\end{array}  
\end{array}  
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== Parameters ==
== Parameters ==
These fixed values are used within the model:
The parameters and scenarios are as in [[D'Onofrio_chemotherapy_model]], the new fixed parameters are


<math>[t_0,t_f]=[0,20], c_1=-1, c_2=0.75, c_3=-2.</math>
<math>(c_{0,1},c_{0,2},c_{0,3},c_{0,4})=(u_0^{max},u_0^{max},0,0) \\
(c_{1,1},c_{1,2},c_{1,3},c_{1,4})=(0,u_0^{max},u_0^{max},0).
</math>


== Reference Solutions ==
== Reference Solutions ==

Revision as of 14:24, 11 January 2018

D'Onofrio model (binary variant)
State dimension: 1
Differential states: 4
Discrete control functions: 4
Path constraints: 2

This site describes a D'Onofrio model variant with four binary controls instead which of only two continuous controls. The continuous controls are replaced via the outer convexifacation method.

Mathematical formulation

For t[t0,tf] the optimal control problem is given by

minx,ux0(tf)+αt0tfu0(t)2dts.t.x˙0=ζx0ln(x0x1)i=14wic1,iFx0,x˙1=bx0μx1dx023x1i=14wic0,iGx1i=14wic1,iηx1,x˙2=i=14wic0,i,x˙3=i=14wic1,i,[1.5ex]x2x2max,x3x3max,1=i=14wi(t),wi(t){0,1},i=14.


Parameters

The parameters and scenarios are as in D'Onofrio_chemotherapy_model, the new fixed parameters are

Failed to parse (syntax error): {\displaystyle (c_{0,1},c_{0,2},c_{0,3},c_{0,4})=(u_0^{max},u_0^{max},0,0) \\ (c_{1,1},c_{1,2},c_{1,3},c_{1,4})=(0,u_0^{max},u_0^{max},0). }

Reference Solutions

If the problem is relaxed, i.e., we demand that w(t) be in the continuous interval [0,1] instead of the binary choice {0,1}, the optimal solution can be determined by means of direct optimal control.

The optimal objective value of the relaxed problem with nt=6000,nu=60 is 1.30167235. The objective value of the binary controls obtained by Combinatorial Integral Approimation (CIA) is 1.30273681.


Source Code

Model description is available in