Open AccessAnalysis of The Efficiency SA (Simulated Annealing) Model And Fuzzy Time Series (Case Study: Inventory System PT Y)
Author(s) -
Riki Ariyanto,
R. Heru Tjahjana,
Titi Udjiani
Publication year - 2021
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 - 10.1088/1742-6596/1776/1/012059
Subject(s) - simulated annealing , warehouse , holding cost , economic shortage , operations research , service level , fuzzy logic , computer science , economic order quantity , inventory control , finished good , anticipation (artificial intelligence) , operations management , mathematical optimization , supply chain , business , economics , microeconomics , engineering , mathematics , marketing , algorithm , linguistics , philosophy , artificial intelligence , production (economics) , government (linguistics)
Forecasting sales and minimizing storage costs is the company’s strategy to maximize inventory in anticipation of sales spikes in stores so that it can be fulfilled even though storage warehouses are limited, on the other hand there is competition among distributors in ordering goods, which is trying to get the maximum level of service from suppliers so warehouse needs can be fullfiled. By using the forecasting method, Chen Fuzzy Time Series to predict future sales combined with the simulation annealing method (simulated annealing algorithm) as an optimization method in order to obtain the lowest possible storage costs. This combination of methods can improve shipping services from warehouse to store as a result of loss sales cause inventory shortages can be controlled so that inventory costs are more minimal and warehouse storage of goods can be maximized, the combination of these methods is more effective than conventional methods available at PT Y