Paper Info
Title
Robust Agricultural Supply Chain Management with Various Random and Fuzzy Parameters
Abstract
This paper proposes a robust model of multiperiod agricultural supply chain to consider both maximizing the total profit and minimizing the environmental load with random and fuzzy parameters. Our proposed model is formulated as a fuzzy and stochastic, multiobjective and multiperiod programming problem, and hence, it is hard to solve the formulated problem directly without setting a specific random distribution and a specific membership function. Therefore, a distribution-free approach based on sample mean and variance derived from received data, which does not assume any specific random distributions and membership functions, is introduced to apply our proposed model to various uncertain conditions. In addition, deterministic equivalent transformations are also introduced to obtain the optimal solution efficiently using the scenario-based approach.
Year
DOI
Venue
2017
10.1109/IIAI-AAI.2017.88
2017 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)
Keywords
Field
DocType
Agricultural supply chain management,Randomness,Fuzziness,Mathematical programming problem,Distribution-free approach
Mathematical optimization,Sample mean and sample covariance,Computer science,Fuzzy logic,Supply chain management,Agriculture,Supply chain,Membership function,Randomness
Conference
ISBN
Citations 
PageRank 
978-1-5386-0622-3
0
0.34
References 
Authors
3
3
Name
Order
Citations
PageRank
Takashi Hasuike110920.39
Tomoko Kashima201.69
Shimpei Matsumoto3109.77