Abstract
Freight transportation has always been a key factor in industry and market supply and expanding markets relies on its efficacy even more. Uncertainty cannot be avoided in transportation, e.g., traffic or navigability of rivers, and stochastic nature impacts contracts between a firm and a transport company. It is essential to analyze the conditions of contracts, whether they have medium or short term validity, e.g., one costs less while other offers more flexibility. Medium term scenario analysis can be formulated as a two-stage decision problem typically handled by methods applying decision trees. Since realistic problems are complex enough to result in a decision tree of enormous size, application of such methods is practically limited. Our study presents a computer aided algorithmic method based on P-graph framework, which is capable to implicitly involve and enumerate all feasible scenarios instead of explicitly enumerate the possibilities, while keeping the problem formulation compact and visible.
Language | English |
---|---|
Pages | 1-11 |
Number of pages | 11 |
Journal | Computers and Chemical Engineering |
Volume | 121 |
DOIs | |
Publication status | Published - Feb 2 2019 |
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Keywords
- Biodiesel
- P-graph
- Stochastic optimization
- Supply chain
- Transportation
ASJC Scopus subject areas
- Chemical Engineering(all)
- Computer Science Applications
Cite this
Process graph approach for two-stage decision making : Transportation contracts. / Konig, Eva; Bertók, B.
In: Computers and Chemical Engineering, Vol. 121, 02.02.2019, p. 1-11.Research output: Contribution to journal › Article
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TY - JOUR
T1 - Process graph approach for two-stage decision making
T2 - Computers and Chemical Engineering
AU - Konig, Eva
AU - Bertók, B.
PY - 2019/2/2
Y1 - 2019/2/2
N2 - Freight transportation has always been a key factor in industry and market supply and expanding markets relies on its efficacy even more. Uncertainty cannot be avoided in transportation, e.g., traffic or navigability of rivers, and stochastic nature impacts contracts between a firm and a transport company. It is essential to analyze the conditions of contracts, whether they have medium or short term validity, e.g., one costs less while other offers more flexibility. Medium term scenario analysis can be formulated as a two-stage decision problem typically handled by methods applying decision trees. Since realistic problems are complex enough to result in a decision tree of enormous size, application of such methods is practically limited. Our study presents a computer aided algorithmic method based on P-graph framework, which is capable to implicitly involve and enumerate all feasible scenarios instead of explicitly enumerate the possibilities, while keeping the problem formulation compact and visible.
AB - Freight transportation has always been a key factor in industry and market supply and expanding markets relies on its efficacy even more. Uncertainty cannot be avoided in transportation, e.g., traffic or navigability of rivers, and stochastic nature impacts contracts between a firm and a transport company. It is essential to analyze the conditions of contracts, whether they have medium or short term validity, e.g., one costs less while other offers more flexibility. Medium term scenario analysis can be formulated as a two-stage decision problem typically handled by methods applying decision trees. Since realistic problems are complex enough to result in a decision tree of enormous size, application of such methods is practically limited. Our study presents a computer aided algorithmic method based on P-graph framework, which is capable to implicitly involve and enumerate all feasible scenarios instead of explicitly enumerate the possibilities, while keeping the problem formulation compact and visible.
KW - Biodiesel
KW - P-graph
KW - Stochastic optimization
KW - Supply chain
KW - Transportation
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U2 - 10.1016/j.compchemeng.2018.07.011
DO - 10.1016/j.compchemeng.2018.07.011
M3 - Article
VL - 121
SP - 1
EP - 11
JO - Computers and Chemical Engineering
JF - Computers and Chemical Engineering
SN - 0098-1354
ER -