Genetic Algorithm Untuk Menyelesaikan Fuzzy Multi-Objective Job Shop Scheduling Problem
Abstrack: Job Shop Scheduling
Problems (JSSP) is a scheduling problem containing of n jobs and m machines
which each job consists of several operations performed by different machines.
Generally, many factors influence the JSSP, but in the real world, the
uncertainty factors such as delays in the working process and the duration of
the operation give effects in determining the schedule. To overcome these
uncertainties, fuzzy number are used for processing time and due date. The
purpose of this skripsi is to solved
Fuzzy Multi-Objective (Agreement Index (AI) and Completion Time) JSSP (FMOJSSP)
by using Genetic Algorithm (GA). The steps of GA are to generating the initial
chromosomes based on the degree of similarity between individuals, evaluation,
tournament selection, crossover and mutation. The program made is implemented
on three datas (problems) of size 6×6 and the best results for mean of AI,
minimum of AI and maximum of completion time for Problem 1 respectively are 0,96186;
0,79422 and (65,0; 87,0; 110,0), for Problem 2 respectively are 0,99227;
0,97460 and (60,0; 83,0; 99,0), for Problem 3 respectively are 0,84864; 0,69231
and (28,0; 38,0; 49,0). Three numbers of completion time sequentially showing
the fastest completion time, the normal completion time and completion time of
late.
Penulis: Marisa, Herry
Suprajitno, Auli Damayanti
Kode Jurnal: jpmatematikadd130071
