Open AccessA sensitivity analysis of stochastic programming for reverse logistic of herbs agro-industry: a case study of herbs logistic in Indonesia
Author(s) -
A. A. Rakhmasari,
Taufik Djatna,
Ono Suparno,
Meika Syahbana Rusli
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/472/1/012055
Subject(s) - solver , logistic regression , fuzzy logic , computer science , sensitivity (control systems) , reverse logistics , data mining , operations research , mathematical optimization , statistics , mathematics , machine learning , artificial intelligence , engineering , marketing , business , electronic engineering , supply chain
This paper analyses the sensitivity of reverse logistic formulation of herbs agro- industry based on fuzzy stochastic mixed integer linear programming. A case study from real world problem of herbs logistic in Indonesia is provided in order to respond stochastic challenges in the reverse logistic system. For implementation purpose of this current progress, some related historical and hypothetical data were deployed. The model was then used to test how far this fuzzy quantitative modelling is capable to solve the problem within available data ranges with consideration on possibility in each data occurrence. A GRG non-linear was used as model solution to solve the fuzzy stochastic modelling with implementation using Excel solver. The fuzzy quantitative modelling result with a case study in herbs logistic in Indonesia is concluded with verification and validation on current model formulation for decision making purposes in herbs reverse logistic.