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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Veröffentlicht in:International journal of fuzzy systems Jg. 22; H. 7; S. 2119 - 2148
1. Verfasser: Sun, Yan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2020
Springer Nature B.V
Schlagworte:
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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Zusammenfassung: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.
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ISSN:1562-2479
2199-3211
DOI:10.1007/s40815-020-00905-x