(untitled) (Economic studies journal, 2024)
The Branch and Bound Method is considered the most important approach for solving integer programming problems. It is particularly useful when the problem’s solution is physically infeasible, meaning the problem’s variables are indivisible. The method begins by finding the non-integer optimal solution (Non-int) and then branching the problem into two subproblems, effectively dividing the feasible solution space into two regions. The optimal solutions for these subproblems are found individually, and the process of branching and solving continues. The branching sequence stops when a subproblem has no feasible solution or when its solution yields integer values. The number of subproblems generated through branching increases significantly with the number of variables and constraints. Sheikh et al. (July 2022) identified criteria for selecting the subproblem most likely to contain the optimal integer solution and stopping the branching for others that do not. In this paper, we propose an additional criterion aimed at reducing the number of branches, where previous criteria have been insufficient. This new criterion can reduce the number of branches by approximately 25%, thereby saving time and effort in solving the problem (pruning the branch tree).