Open AccessOptimization of Production Scheduling and Actual Stock Using Fuzzy Genetic Algorithm
Author(s) -
Cut Try Utari,
Muhammad Zarlis,
Sutarman Sutarman
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1235/1/012035
Subject(s) - computer science , fuzzy logic , mathematical optimization , fair share scheduling , dynamic priority scheduling , genetic algorithm scheduling , rate monotonic scheduling , algorithm , mathematics , artificial intelligence , computer network , schedule , quality of service , operating system
In this case, fuzzy is applied as a determination optimization of actual stock. Based on the research that has been done, solving the problem of scheduling and actual stock optimization with Fuzzy Genetic Algorithm method has better performance than non-fuzzy Genetic Algorithm method. Production scheduling with Fuzzy Genetic Algorithm shows faster process result. Seen from the iteration that occurs is 1 (one) for scheduling with Fuzzy while on non fuzzy production scheduling, the process is completed in the iteration to 34. Scheduling with Fuzzy also shows better optimum percentage that is with 100% average while in non fuzzy production scheduling is 97%.