Integer Linear Programming (ILP) Solution Using Branch and Bound Method
Problem Statement
We need to solve the following Integer Linear Programming (ILP) problem:
Maximize:
Subject to:
must be integers.
Solution Using Branch and Bound Method
Step 1: Solve the Linear Relaxation (Ignore Integer Constraints)
First, we solve the problem as a standard Linear Program (LP) without integer constraints.
Graphical Approach
Constraint 1:
When ,
When ,
Constraint 2:
When , (Not feasible since )
When ,
Feasible Corner Points:
→
→
Intersection of Constraints:
Solving:
Solution: , →
→
Optimal LP Solution:
Since is not integer, we proceed with Branch and Bound.
Step 2: Branching on
We branch on the non-integer variable , creating two subproblems:
Subproblem 1:
Subproblem 2:
Subproblem 1 ()
New Constraints:
Solution:
Intersection of and :
Optimal LP Solution: ,
Since is still non-integer, we branch further on :
Branch
New Solution: ,
Feasible Integer Solution!
Current Best:
Branch
New Solution: →
Still non-integer, but .
Further branching needed, but we prune since it cannot exceed .
Subproblem 2 ()
New Constraints:
Solution:
Intersection of and :
Optimal LP Solution: ,
Since is non-integer, we branch further on :
Branch
New Solution: ,
Still non-integer, but .
Further branching possible, but we prune since it cannot exceed .
Branch
New Solution:
,
Still non-integer, but .
Prune since it cannot exceed .
Step 3: Compare All Feasible Integer Solutions
From the branching steps, the feasible integer solutions found are:
→
→ (Check feasibility: , )
Best Integer Solution:
Final Answer
The optimal integer solution is:
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