Browsing by Author "Ardiansyah, Muhammad Nashir"

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A decision model for last-mile delivery planning with crowdsourcing integration
(2019-09-01)
Huang, Kuancheng
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Ardiansyah, Muhammad Nashir
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
Crowdsourced transportation has been playing a more important role when faced with the growing demand for last-mile delivery, mainly due to the booming e-commerce. Crowdsourced delivery offers greater flexibility and requires less capital investment than traditional outsourcing approaches. This study deals with the planning of the last-mile delivery with partial crowdsourcing integration, in which crowdsourcing helps to manage the delivery from a transfer point to final customer locations. The decision involves several basic questions, including which customer is to be outsourced, by which outsourcing partner, and at which transfer point. The decision problem is formulated as a mixed integer programing (MIP) model. In addition, a heuristics algorithm has been designed to handle large-scale problems. Based on the numerical experiment, the heuristics algorithm can generate a good quality solution within an acceptable computation time. In general, this study shows that well-planned crowdsourcing integration can take advantage of the flexibility and cost saving of crowdsourcing for last-mile delivery.
A mathematical programming model for aircraft leasing decisions
(2018-06-01)
Chen, Wei-Ting
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Huang, Kuancheng
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Ardiansyah, Muhammad Nashir
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運輸與物流管理系註：原交通所+運管所
;
Department of Transportation and Logistics Management
For the airline fleet planning problem, this paper formulates a mathematical programming model specifically also taking into account of the increasingly popular capital lease, which has some mixed features of the two traditional aircraft acquirement methods: operating lease and purchase. Given the aircraft requirements, budget, and debt-ratio limit, the objective is to minimize the total cost within the planning horizon. Numerical experiments were conducted to compare the optimal solutions for the airlines with different business models, scales, and experiences. This paper further simulates a scenario under the new standards which will be applied in 2019. The results of sensitivity analysis show that when the debt-ratio constraint is relaxed, capital leases would be helpful for reducing the cost of airlines.
A stochastic dairy transportation problem considering collection and delivery phases
(2019-09-01)
Huang, Kuancheng
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Wu, Kun-Feng
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Ardiansyah, Muhammad Nashir
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運輸與物流管理系註：原交通所+運管所
;
Department of Transportation and Logistics Management
Based on the dairy cooperatives in Indonesia, this study formulates a stochastic programming model to handle the milk collection and delivery process with the maximum route duration limitation, the external cooling facility option, and travel time uncertainty. Besides, the local practice of sharing the fleet for both collection and delivery further complicates the decision. A set covering-based solution approach is used, due to its flexibility in handling complicated operational requirements and alignment with the decision environment. According to the numerical experiment, the proposed solution algorithm can provide quality solutions with a reasonable computational time for the cooperative operators.
An evaluation scheme for assessing the effectiveness of intersection movement assist (IMA) on improving traffic safety
(2018-01-01)
Wu, Kun-Feng
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Ardiansyah, Muhammad Nashir
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Ye, Wei-Jyun
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運輸與物流管理系註：原交通所+運管所
;
Department of Transportation and Logistics Management
Objective: Intersection movement assist (IMA) has been recognized as one of the prominent countermeasures to reduce angle crashes at intersections, which constitute 22% of total crashes in the United States. Utilizing vehicle-based sensors, vehicle-to-vehicle (V2V), and vehicle-to-infrastructure (V2I) communications, IMA offers extended vision to provide early warning for an imminent crash. However, most of IMA-related research implements their methods and strategies only in simulations, test tracks, or driving simulator studies that have quite a few assumptions and limitations and hence the effectiveness evaluations reported may not be transferable or comparable.Methods: This study seeks to develop a generalized evaluation scheme that can be used not only to assess the effectiveness of IMA on improving traffic safety at intersections but to facilitate comparisons across similar studies. The proposed evaluation scheme utilizes the concepts of traffic conflict in terms of time-to-collision (TTC) as a crash surrogate. This approach avoids the issue of having insufficient crash frequency data for system evaluation. To measure the effectiveness of IMA on reducing traffic conflicts, a relative risk is calculated for comparing the risk of with/without using the IMA. As a proof-of-concept study, this study applied the proposed evaluation scheme and reported the effectiveness of IMA on improving traffic safety in a field operation test (FOT). Seven test scenarios were conducted at 4 intersections, and a total of 40 participants were recruited to use the IMA for 6months.Results: It was estimated that IMA users have 26% fewer conflicts with TTC less than 5s and have 15% fewer conflicts with TTC less than 4s. However, the results vary across different sites and different definitions of conflicts in terms of TTC.Conclusions: Overall, IMA is promising to effectively reduce angle crashes related to sight obstruction and has potential to reduce not only crash frequency but crash severity.
Identify sequence of events likely to result in severe crash outcomes
(2016-11-01)
Wu, Kun-Feng
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Thor, Craig P.
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Ardiansyah, Muhammad Nashir
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運輸與物流管理系註：原交通所+運管所
;
Department of Transportation and Logistics Management
The current practice of crash characterization in highway engineering reduces multiple dimensions of crash contributing factors and their relative sequential connections, crash sequences, into broad definitions, resulting in crash categories such as head-on, sideswipe, rear-end, angle, and fixed-object. As a result, crashes that are classified in the same category may contain many different crash sequences. This makes it difficult to develop effective countermeasures because these crash categorizations are based on the outcomes rather than the preceding events. Consequently, the efficacy of a countermeasure designed for a specific type of crash may not be appropriate due to different pre-crash sequences. This research seeks to explore the use of event sequence to characterize crashes. Additionally, this research seeks to identify crash sequences that are likely to result in severe crash outcomes so that researchers can develop effective countermeasures to reduce severe crashes. This study utilizes the sequence of events from roadway departure crashes in the Fatality Analysis Reporting System (FARS), and converts the information to form a new categorization called "crash sequences." The similarity distance between each pair of crash sequences were calculated using the Optimal Matching approach. Cluster analysis was applied to group crash sequences that are etiologically similar in terms of the similarity distance. A hybrid model was constructed to mitigate the potential sample selection bias of FARS data, which is biased toward more severe crashes. The major findings include: (1) in terms of a roadway departure crash, the crash sequences that are most likely to result in high crash severity include a vehicle that first crosses the median or centerline, runs-off-road on the left, and then collides with a roadside fixed-object; (2) seat-belt and airbag usage reduces the probability of dying in a roadway departure crash by 90%; and (3) occupants who are seated on the side of the vehicle that experience a direct impact are 2.6 times more likely to die in a roadway departure crash than those not seated on the same side of the vehicle where the impact occurs. (C) 2016 Elsevier Ltd. All rights reserved.