PENDEKATAN ALGORITMA GENETIKA DALAM MENYELESAIKAN PERMASALAHAN FUZZY LINEAR PROGRAMMING
Abstract: Fuzzy linear
programming is one of the linear programming developments which able to
accommodate uncertainty in the real world. Genetic algorithm approach in
solving linear programming problems with fuzzy constraints has been introduced
by Lin (2008) by providing a case which consists of two decision variables and
three constraint functions. Other linear programming problem arise with the
presence of some coefficients which are fuzzy in linear programming problems,
such as the coefficient of the objective function, the coefficient of
constraint functions, and right-hand side coefficients constraint functions. In
this study, the problem studied is to explain the genetic algorithm approach to
solve linear programming problems where the objective function coefficients and
right-hand sides are fuzzy constraint functions.
PT Dakota Furniture study case provides a linear programming formulation
with a given objective function coefficients and right-hand side coefficients
are fuzzy constraint functions. This study describes the use of genetic
algorithm approach to solve the problem of linear programming of PT Dakota to
maximize the mean income. The genetic algorithm approach is done by simulate
every fuzzy number and each fuzzy numbers by distributing them on certain
partition points. Then genetic algorithm is used to evaluate the value for each
partition point. As a result, the Final Value represents the coefficient of
fuzzy number. Fitness function is done
by calculating the value of the objective function of linear programming
problems. Empirical results indicated that the genetic algorithm approach can
provide a very good solution by giving some limitations on each fuzzy
coefficient.
Genetic algorithm approach can be extended not only to resolve the case
of PT Dakota Furniture, but can also be used to solve other linear programming
case with some coefficients in the objective function and constraint functions
are fuzzy.
Penulis: Siska Dewi Lestari,
Subanar
Kode Jurnal: jptinformatikadd110172
