Row Generation Technique to Solve the Problems of Capital Budgeting Allocation under Combinatorial Constraints
This research aims to study capital budgeting allocation under very large combinatorial constraints to consider all alternatives of project investments under limited resources using the row generation technique. The amount of combinatorial constraints in mathematical model of this research is equal to 2N-1 where N is the number of projects. If problems of capital budgeting allocation occur due to many projects, many constraints will follow accordingly. As a result, the mathematical model will consist of a very large N and may have difficulty in solving the problems. Therefore, the researchers apply the row generation technique to reduce a number of constraints of capital budgeting allocation down to the number of constraints necessary to find the answers. The results indicate that the row generation technique uses less processing time than the linear programming with over 12 projects. For example, for 20 projects, the processing time to solve the problems by using the linear programming technique is more than 48 hours. On the other hand, for 50 projects, the processing time to solve the problems by using the row generation technique is less than 5 minutes.
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