### Problem 6

A population growth model due to Cooke et alia [3] describes the population y(t) at time t by the equation
 y¢(t) = b  e-a y(t-T) y(t-T) e-d1 T - d y(t)
Solve the equation on [0,25] with history y(t) = 3.5 for t £ 0 for one or more of the data sets

1. a = 1, d = 1, d1 = 1, b = 20
2. a = 1, d = 1, d1 = 1, b = 80
3. a = 1, d = 1, d1 = 0, b = 20
4. a = 1, d = 1, d1 = 0, b = 80

For each set of parameter values, solve the problem using three values of the delay, namely T = 0.2,1.0, 2.4 , and plot the solutions on the same figure. Structures can be indexed, so this can be coded as

```  for i = 1:3
T = Delays(i);
sol(i) = dde23('prob6f',T,3.5,[0, 25],opts);
end
```
On exit from the loop, the solution for the first delay is sol(1).x,sol(1).y and so forth. Note that T must be communicated to prob6f as a parameter or global variable because it appears in the equation. In the code fragment it is communicated as a global variable along with the parameters of the data set. You should use tolerances more stringent than the defaults, e.g.,
```opts = ddeset('RelTol',1e-5,'AbsTol',1e-8);
```
You might find it interesting to compare your solutions with those of Figure 3 in [3]. The following figures show the solutions for two of the data sets. Obviously the delay has a profound effect on the solution.

### Reference

[3]
K. Cooke, P. van den Driessche, and X. Zou, Interaction of maturation delay and nonlinear birth in population and epidemic models, J. Math. Biol., 39 (1999) 332-352.