Use Python 2.7 and I need the code!

Assignment overview. The purpose of this assignment is to illustrate how you can use your programming skills to combine analytical and numerical approaches to perform cost-benefit analysis. Specifically, we consider a system which allows for a closed-form solution, and then use it to optimize system parameters Directions: 1. Example 6.13 on page 377 in the book (A machine repair model) considers a job shop that consists of M independent identical machines and one service man. Among other observations, the book provides analytical formulas for long-run proportions: Pn. Implement function Pn that takes values for parameters , , M and n and returns the long-run proportion P, for this model. def Pn (Lambda, Mu, M. n): p- return p Note also that you can find factorial n! by defining function: def factorial (n): If n== 0: return 1 else return nfactorial(n-1) 2. Now, suppose that there are costs associated with each state. The costs could include: operational costs depending on the number of machines, repair costs, penalty for having no machines running, and purchasing cost of additional machines. Your second task is to find the optimal number of machines for a simple cost profile. (a) Obtain values for parameters by following links: , http://www.wolframalpha . com/input/?itw0+ random-numbers++from+50+to+100 c1 http://www.wolframalpha.com/input/?i-random+number+from+800+to+5000 c2 http://www.wolframalpha.com/input/?i-random+number++from+1+to+10 (b) Suppose each machine has a daily cost of ci. Further, c2 is the cost of having no running ma- g in state M) per day. Assignment overview. The purpose of this assignment is to illustrate how you can use your programming skills to combine analytical and numerical approaches to perform cost-benefit analysis. Specifically, we consider a system which allows for a closed-form solution, and then use it to optimize system parameters Directions: 1. Example 6.13 on page 377 in the book (A machine repair model) considers a job shop that consists of M independent identical machines and one service man. Among other observations, the book provides analytical formulas for long-run proportions: Pn. Implement function Pn that takes values for parameters , , M and n and returns the long-run proportion P, for this model. def Pn (Lambda, Mu, M. n): p- return p Note also that you can find factorial n! by defining function: def factorial (n): If n== 0: return 1 else return nfactorial(n-1) 2. Now, suppose that there are costs associated with each state. The costs could include: operational costs depending on the number of machines, repair costs, penalty for having no machines running, and purchasing cost of additional machines. Your second task is to find the optimal number of machines for a simple cost profile. (a) Obtain values for parameters by following links: , http://www.wolframalpha . com/input/?itw0+ random-numbers++from+50+to+100 c1 http://www.wolframalpha.com/input/?i-random+number+from+800+to+5000 c2 http://www.wolframalpha.com/input/?i-random+number++from+1+to+10 (b) Suppose each machine has a daily cost of ci. Further, c2 is the cost of having no running ma- g in state M) per day