Linear Programming Problem Setup

In summary, the constraints need to be defined to set up the problem. The attempt at a solution is to minimize Z.
  • #1
nikki__10234
3
0
We were given this problem in a Linear Programming class and asked to define the constraints.

Homework Statement



max Z = max (xεS) {min {Z1, Z2...Zq}}

where Zi=C1ix1 + C2ix2+...+Cnixn


Homework Equations



Constraints need to be defined to set up the problem.

The Attempt at a Solution



The first few Z equations would be:
Z1=C11x1 + C21x2+...+Cn1xn

Z2=C12x1 + C22x2+...+Cn2xn

Zq=C1qx1 + C2qx2+...+Cnqxn

I think the best way to ensure that the Z is at a minimum is to define the inequalities below:
Z < Z1
Z < Z2
...
Z < Zq

This ensures that we pick the minimum value of Z. But these constraints should also include some way to maximize x and I am confused as to how to include that.
 
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  • #2
nikki__10234 said:
We were given this problem in a Linear Programming class and asked to define the constraints.

Homework Statement



max Z = max (xεS) {min {Z1, Z2...Zq}}

where Zi=C1ix1 + C2ix2+...+Cnixn


Homework Equations



Constraints need to be defined to set up the problem.

The Attempt at a Solution



The first few Z equations would be:
Z1=C11x1 + C21x2+...+Cn1xn

Z2=C12x1 + C22x2+...+Cn2xn

Zq=C1qx1 + C2qx2+...+Cnqxn

I think the best way to ensure that the Z is at a minimum is to define the inequalities below:
Z < Z1
Z < Z2
...
Z < Zq

This ensures that we pick the minimum value of Z. But these constraints should also include some way to maximize x and I am confused as to how to include that.

As written, your formulation will fail, but it can be modified slightly to work properly. Come back for additional hints when you have dealt with this issue.

RGV
 
  • #3
Would it work to write the constraints as follows instead of saying Z<Zi. This way you are telling the program to choose the maximum values of x that lead to the minimum Z.

Z ≤ c11x1+...+c1nxn

Z ≤ c21x1+...+c2nxn

...

Z ≤ cq1x1+...+cqnxn
 
  • #4
nikki__10234 said:
Would it work to write the constraints as follows instead of saying Z<Zi. This way you are telling the program to choose the maximum values of x that lead to the minimum Z.

Z ≤ c11x1+...+c1nxn

Z ≤ c21x1+...+c2nxn

...

Z ≤ cq1x1+...+cqnxn

Why would you want to minimize Z? You were asked to maximize the minimum, not minimize it. Anyway, as written your problem would be unbounded, with Zmin = -∞.

RGV
 

Related to Linear Programming Problem Setup

1. What is a linear programming problem setup?

A linear programming problem setup is a mathematical method used to find the optimal solution to a problem that involves maximizing or minimizing a linear objective function subject to a set of linear constraints. It involves formulating the problem in terms of decision variables, an objective function, and constraints, and then using mathematical techniques to find the best possible solution.

2. What are decision variables in linear programming?

Decision variables are the unknown quantities that we are trying to determine in a linear programming problem. They represent the choices or decisions that we need to make in order to optimize the objective function. These variables can be assigned values that satisfy the constraints and maximize or minimize the objective function.

3. How do constraints affect a linear programming problem setup?

Constraints play a crucial role in a linear programming problem setup as they limit the possible values that the decision variables can take. These constraints can be inequalities or equations that represent the limitations or requirements of the problem. They help in finding the feasible region, which is the set of all possible solutions that satisfy the constraints.

4. What is an objective function in linear programming?

An objective function is a linear expression that represents the quantity we want to maximize or minimize in a linear programming problem. It is usually stated in terms of the decision variables and represents the goal or objective of the problem. The objective function can be in the form of a maximization or minimization problem, depending on the problem setup.

5. How is a linear programming problem solved?

A linear programming problem is typically solved using algorithms and mathematical techniques. The most commonly used method is the simplex method, which involves systematically moving from one feasible solution to another until the optimal solution is reached. Other methods include the dual simplex method, interior point method, and the branch and bound method, among others.

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