Modification Goal Programming for Solving Multi-Objective De Novo Programming Problems
Febrianto Afli,
Ihda Hasbiyati,
Moh Danil Hendry Gamal
Issue:
Volume 5, Issue 4, December 2019
Pages:
64-69
Received:
25 October 2019
Accepted:
15 November 2019
Published:
21 November 2019
Abstract: Many methods can be used to solve multi-objective problems, but not all of them provide truly optimal results because there are still deviations and inefficient use of resources so that they still produce residuals. Resources that are not used in their entirety can reduce the level of optimization in solving multi- objective problems. This happens because we are too forced to solve existing problems rather than redesigning the problem so that it gets satisfactory results. One method that can be used to solve this problem is by using the de novo program. The de novo programming aims to design a more optimal system by expanding resources based on available budgets. The de novo programming changes the function of constraints into form of a budget. This change into one constraint function makes in the feasible solution changes. So it is important to determine the goal for all objectives that have the same importance so that all objectives are achieved at the optimum condition. The objectives of the goals to be achieved must be determined in advance in resolving multi-objective problems. This paper proposes determining the goal objectives using the average concept for objectives that have the same interests. Determination of goals with an averageeachconcept considers the objectives of other goals in determining a goal. Determination of goal objectives using the average concept applied to the goal programming to solve the multi-objective problem of the de novo programming. Solution to the de novo program's multi-objective problem using a modified goal program. The computational results with benchmarking problems show that the proposed method gives satisfactory results and more practical work.
Abstract: Many methods can be used to solve multi-objective problems, but not all of them provide truly optimal results because there are still deviations and inefficient use of resources so that they still produce residuals. Resources that are not used in their entirety can reduce the level of optimization in solving multi- objective problems. This happens ...
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