Reliable facility location design with round-trip transportation under imperfect information Part I: A discrete model

Liu, Yun; Wang, Xifu; Fan, Hongqiang; Li, Xiaopeng

doi:10.1016/j.tre.2019.101825

Cited by 8 publications

(3 citation statements)

References 44 publications

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“…Several modeling approaches can be leveraged to tackle these future research opportunities in the air taxi domain. Typically mathematical models, such as linear programming, mixedinteger programming, and dynamic programming, are used for optimizing decisions like pricing, fleet procurement, facility location, maintenance scheduling, and workforce allocation Corberán et al, 2020;Yun et al, 2020). Likewise, to obtain scalable and computationally efficient solutions for large-scale problems, prior research has also used simulation (e.g., discrete-event systems simulation and agent-based simulation), heuristic approaches (e.g., neighborhood search algorithms, greedy randomized adaptive search procedure) and meta-heuristic algorithms (e.g., genetic algorithms, simulated annealing).…”

Section: Opportunities For Future Research Directionsmentioning

confidence: 99%

Air taxi service for urban mobility: A critical review of recent developments, future challenges, and opportunities

Rajendran

Srinivas

2020

Transportation Research Part E: Logistics and Transportation Re

122

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Expected to operate in the imminent future, air taxi service (ATS) is an aerial on-demand transport for a single passenger or a small group of riders, which seeks to transform the method of everyday commute. This uncharted territory in the emerging transportation world is anticipated to enable consumers bypass traffic congestion in urban road networks. By adopting an electric vertical takeoff and landing concept (eVTOL), air taxis could be operational from skyports retrofitted on building rooftops, thus gaining advantage from an implementation standpoint. Motivated by the potential impact of ATS, this study provides a review of air taxi systems and associated operations. We first discuss the current developments in the ATS (demand prediction, air taxi network design, and vehicle configuration). Next, we anticipate potential future challenges of ATS from an operations management perspective, and review the existing literature that could be leveraged to tackle these problems (ride-matching, pricing strategies, vehicle maintenance scheduling, and pilot training and recruitment). Finally, we detail future research opportunities in the air taxi domain.

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Section: Opportunities For Future Research Directionsmentioning

confidence: 99%

Air taxi service for urban mobility: A critical review of recent developments, future challenges, and opportunities

Rajendran

Srinivas

2020

Transportation Research Part E: Logistics and Transportation Re

122

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“…On the other hand, under imperfect information, customers do not know facilities' states. They have to visit a series of pre-assigned facilities until they find a functioning facility to get the service or return with no service (Yun et al, 2020). It is usual for customers not to have enough information about the disruptions in facilities.…”

Section: Introductionmentioning

confidence: 99%

A meta heuristic approach for reliable capacitated facility joint inventory-location problem with round-trip transportation under imperfect information of disruption in a Fuzzy environment

et al. 2022

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In today’s systems and networks, disruption is inevitable. Designing a reliable system to overcome probable facility disruptions plays a crucial role in planning and management. This article proposes a reliable capacitated facility joint inventory-location problem where location-independent disruption may occur in facilities. The system tries to satisfy customer's demands and considers penalty costs for unmet customer demand. The article aims to minimize total costs such as establishing inventory, uncovered demand’s penalty, and transportation costs. While many articles in this area only use exact methods to solve the problem, this article uses a metaheuristic algorithm, the red deer algorithm, and the exact methods. Various numerical examples have shown the outstanding performance of the red deer algorithm compared to exact methods. Sensitivity analyses show the impacts of various parameters on the objective function and the optimal facility layouts. Lastly, managerial insights will be proposed based on sensitivity analysis.

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“…The selection of an integrated transport hub in a multimode transportation network should consider not only the economics of transportation but also the vulnerability of the network to extreme conditions [1]. For example, during the smog weather in North China in December 2017, a large number of passengers who needed to fly to Beijing had to continue their journey by train after landing in other cities.…”

Section: Introductionmentioning

confidence: 99%

Mitigating the Vulnerability of a High-Speed Railway–Air Network by Optimizing the Location of Integrated Transportation Hubs

et al. 2022

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High-speed trains and flights are the backbone of interregional transportation. A coupled highspeed railway-air transportation network (HRATN) allows these two modes of transportation to substitute for each other when the HRATN is threatened by extreme events. During train and flight operations, the area of influence and occurrence of extreme events are difficult to predict. Reasonably selected integrated transportation hubs can mitigate the vulnerability of HRATNs to extreme events. Optimizing the locations of integrated transportation hubs makes full use of the transport resources of both modes and facilitates the transfer of passengers, thereby decreasing the losses caused by extreme events. In this research, a tri-level model is established to reduce the potential worst loss by optimizing the location of the integrated transportation hub. The column-and-constraint generation algorithm based on duality is used to solve the model. For an illustrative example case, the enumeration method and sensitivity analysis show that building more integrated hubs can mitigate HRATN vulnerability but decreases unit investment income. This trivial conclusion verifies the validity of the model constructed in this paper. For a real-world case, comparing the corresponding models that do not consider extreme events reveals that the proposed strategy does not conflict with the decision-making in the normalized situation, thus verifying the usability of the present research.

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Reliable facility location design with round-trip transportation under imperfect information Part I: A discrete model

Cited by 8 publications

References 44 publications

Air taxi service for urban mobility: A critical review of recent developments, future challenges, and opportunities

Air taxi service for urban mobility: A critical review of recent developments, future challenges, and opportunities

A meta heuristic approach for reliable capacitated facility joint inventory-location problem with round-trip transportation under imperfect information of disruption in a Fuzzy environment

Mitigating the Vulnerability of a High-Speed Railway–Air Network by Optimizing the Location of Integrated Transportation Hubs

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