Fuzzy Approaches and Simulation-Based Reliability Modeling to Solve a Road–Rail Intermodal Routing Problem with Soft Delivery Time Windows When Demand and Capacity are Uncertain

In this study, a freight routing problem considering both soft delivery time windows and demand and capacity uncertainty in a road–rail intermodal transportation system is investigated. According to fuzzy set theory, uncertain demands and capacities are formulated as trapezoidal fuzzy numbers. Soft...

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Vydané v:	International journal of fuzzy systems Ročník 22; číslo 7; s. 2119 - 2148
Hlavný autor:	Sun, Yan
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2020 Springer Nature B.V
Predmet:	Artificial Intelligence Computational Intelligence Costs Customer services Demand Engineering Fuzzy logic Fuzzy set theory Fuzzy sets Integer programming Intermodal Intermodal transportation Management Science Mixed integer Nonlinear programming North American Free Trade Agreement Operations Research Optimization Parameters Reliability analysis Roads & highways Routing Schedules Simulation Transportation services Transportation systems Windows (intervals) Road–rail intermodal routing Fuzzy chance-constrained programming Fuzzy programming model Fuzzy expected value Soft time windows Simulation-based reliability Fuzzy ranking Capacity uncertainty Demand uncertainty
ISSN:	1562-2479, 2199-3211
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Abstract	In this study, a freight routing problem considering both soft delivery time windows and demand and capacity uncertainty in a road–rail intermodal transportation system is investigated. According to fuzzy set theory, uncertain demands and capacities are formulated as trapezoidal fuzzy numbers. Soft delivery time windows under a fuzzy environment is established, in which fuzzy periods caused by early and late deliveries that lead to penalty are modeled based on maximum functions. To solve the routing problem yielding the above characteristics, this study designs a fuzzy mixed-integer nonlinear programming model whose objective is to minimize the total costs created in the road–rail intermodal transportation activities. After using the fuzzy expected value method to address the fuzzy objective, two fuzzy approaches, i.e., fuzzy chance-constrained programming method and fuzzy ranking method, are separately adopted to undertake the defuzzification of the fuzzy constraints. Improved linear formulations of the model are then produced to make it easier to solve. A simulation-based reliability modeling is developed to quantify the reliability of the optimization results given by different fuzzy approaches under different parameter settings in a simulation environment. Finally, an empirical case is presented to verify the feasibility of the proposed methods. The effects of demand and capacity fuzziness on the routing optimization are revealed, and an optimization procedure that helps decision-makers to select a more suitable fuzzy approach and determine the best parameter setting for a given case is demonstrated. Some insights that are helpful for organizing a reliable transportation are also drawn.
AbstractList	In this study, a freight routing problem considering both soft delivery time windows and demand and capacity uncertainty in a road–rail intermodal transportation system is investigated. According to fuzzy set theory, uncertain demands and capacities are formulated as trapezoidal fuzzy numbers. Soft delivery time windows under a fuzzy environment is established, in which fuzzy periods caused by early and late deliveries that lead to penalty are modeled based on maximum functions. To solve the routing problem yielding the above characteristics, this study designs a fuzzy mixed-integer nonlinear programming model whose objective is to minimize the total costs created in the road–rail intermodal transportation activities. After using the fuzzy expected value method to address the fuzzy objective, two fuzzy approaches, i.e., fuzzy chance-constrained programming method and fuzzy ranking method, are separately adopted to undertake the defuzzification of the fuzzy constraints. Improved linear formulations of the model are then produced to make it easier to solve. A simulation-based reliability modeling is developed to quantify the reliability of the optimization results given by different fuzzy approaches under different parameter settings in a simulation environment. Finally, an empirical case is presented to verify the feasibility of the proposed methods. The effects of demand and capacity fuzziness on the routing optimization are revealed, and an optimization procedure that helps decision-makers to select a more suitable fuzzy approach and determine the best parameter setting for a given case is demonstrated. Some insights that are helpful for organizing a reliable transportation are also drawn.
Author	Sun, Yan
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Snippet	In this study, a freight routing problem considering both soft delivery time windows and demand and capacity uncertainty in a road–rail intermodal...
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SubjectTerms	Artificial Intelligence Computational Intelligence Costs Customer services Demand Engineering Fuzzy logic Fuzzy set theory Fuzzy sets Integer programming Intermodal Intermodal transportation Management Science Mixed integer Nonlinear programming North American Free Trade Agreement Operations Research Optimization Parameters Reliability analysis Roads & highways Routing Schedules Simulation Transportation services Transportation systems Windows (intervals)
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Title	Fuzzy Approaches and Simulation-Based Reliability Modeling to Solve a Road–Rail Intermodal Routing Problem with Soft Delivery Time Windows When Demand and Capacity are Uncertain
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