Open AccessAfrican Buffalo Optimization for Solving Flow Shop Scheduling Problem to Minimize Makespan
Author(s) -
Maria Krisnawati,
Ayu Anggraeni Sibarani,
Anita Mustikasari,
Demaspira Aulia
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/982/1/012061
Subject(s) - job shop scheduling , particle swarm optimization , mathematical optimization , flow shop scheduling , computer science , metaheuristic , scheduling (production processes) , heuristic , multi swarm optimization , mathematics , schedule , operating system
In this paper, African Buffalo Optimization is proposed to solve the flow-shop Scheduling Problem (FSP). The FSP involves n-job that was processed in m-machine. The aim is to reduce the makespan of the whole process. In this study, we also compare the African Buffalo Optimization with an exact solution and other meta-heuristic methods, such as Particle Swarm Optimization (PSO), Hybrid Genetics Algorithm, and also Crow-search Algorithm (CSA) to know the performance of the methods in solution quality and computational time. Friedman test showing African Buffalo Optimization gives an optimal solution in solution quality, the same result with the exact solution, PSO, and hybrid GA.