Faster Algorithms for the Quickest Transshipment Problem

Fleischer, Lisa

doi:10.1137/s1052623497327295

Cited by 62 publications

(59 citation statements)

References 23 publications

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“…The model may be useful for the case with no waiting time also. The problem can be extended to the problem with multiple nodes in the disaster and the safety zones with no waiting time [9] .A pseudo polynomial time solution exists for the problem with time dependent attributes having single node disaster and safety zone. The attributes transit time, transit cost, transit capacities, storage cost and capacities can be taken into account for the time dependent case.…”

Section: Optimization Approachmentioning

confidence: 99%

“…Such flow always exists if there is only one node of the safety zone. There may not be a maximum dynamic flow with earliest arrival case if more than one node in the safety zone occurs [9]. However, Earliest arrival owes from multiple sources to a single sink do always exist [10].An additional constraint of flow for each node in the disaster and the safety zone is taken for the problem with more than one node in the disasters and the safety zones.…”

Section: Optimization Approachmentioning

confidence: 99%

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Optimal Traffic Planning for Efficient Evacuation

Khadka

2016

J. Adv. Coll. Engin. Mgt.

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Efficient traffic planning during evacuation in emergency has been important issue. The planning based on research significantly improves the quality of the emergency management. In this paper, we discuss on both optimization and simulation approaches of the traffic planning. Both approaches have been extensively studied in the literature with efficient softwares. Keywords: Traffic planning, evacuation planning, emergency management ____________________________________________________________________________________________________ IntroductionEmergency management deals with natural and man-made disasters with the goal of saving lives and protecting property during emergencies and disasters. The management based on research upgrades the quality. Nepal has been a vulnerable place for disasters such as earthquake, flood, land slide, explosion of glacial lakes, fire etc. The country has been suffering from such disasters like flood, land slide, fire every year and has been losing a good number of lives and property. Emergency management does not avert or eliminate the threats themselves. However, the study and prediction of the threats based on research substantially reduce the risk.One of the most important issues in the emergency management is to plan effective transportation mode which can evacuates within a reasonable time. The traffic planning during the response phase of the emergency management has been extensively studied in the literature on both optimization as well as simulation approaches, see [6].In this paper, we describe both optimization and simulation approaches in brief that exist in the literature.The organization of the paper is as follows. We describe about emergency management in Section 2, evacuation planning in Section 3, traffic planning in Section 4. We give a brief report of the optimization and simulation approaches for the traffic planning. The last section concludes the paper. Emergency ManagementEmergency management includes prevention, planning, response and recovery (PPRR) in order to lessen the impact of disasters.Prevention is designed to provide permanent protection from disasters though not all disasters can be prevented. The risk of loss can be lessened. It is not worthy that the Hyogo Framework has been adopted on 2005 by 168 Governments as a 10-year global plan for natural disaster risk reduction.

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Section: Optimization Approachmentioning

confidence: 99%

Section: Optimization Approachmentioning

confidence: 99%

Optimal Traffic Planning for Efficient Evacuation

Khadka

2016

J. Adv. Coll. Engin. Mgt.

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“…UQF was first proposed by Gale, who showed the existence of such a flow pattern in a single-source, single-sink network (21). UQF does not necessarily exist in a multisource multisink network (22). For a single-sink network with multiple sources, however, the UQF does always exist (23).…”

Section: Assigning Routes For Evacuees From Safe Zones To Final Destimentioning

confidence: 99%

Modeling of Evacuation and Background Traffic for Optimal Zone-Based Vehicle Evacuation Strategy

Zheng

Chiu

Mirchandani

et al. 2010

Transportation Research Record: Journal of the Transportation R

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Supply-demand interaction is a challenge that must be considered in no-notice evacuation modeling. It is quite common that during an evacuation event, demand is much greater than supply for an extended time period, resulting in severe and prolonged traffic congestion. The severity and temporal extent of such congestion cannot be estimated by simple calculation because of the traffic flow phenomenon in which the traffic throughput is much less than the nominal capacity under severe congestion. Even more, evacuees change their decisions before or during evacuation in response to various traffic management strategies, such as radio and message sign information or contraflow lanes and improved signal control. Once the traffic management decisions are modified, the traffic demand on various evacuation routes would change, as does the congestion resulting from this new demand-supply interaction.The system performance of such an interaction can be properly captured through a descriptive traffic simulation model combined with a prescriptive optimization model for the evacuation strategies. The selection and implementation of no-notice evacuation strategies need to be driven by one or several system objectives. In the prescriptive concept, the best possible strategy is then established through a system optimization approach.Most traditional prescriptive models use only static flow without considering vehicular flow dynamics, such as shock wave propagation or queue formation and dissipation. In recent years, the cell transmission model (CTM) (1) has been used as part of the system-optimal (SO) dynamic traffic assignment (DTA) method (2) in several evacuation studies (3,4), to determine the multidimensional optimal decisions simultaneously, including evacuees' departure time, destination, and route choices (5).The "information" component is another important element that needs to be properly captured in evacuation modeling. Chiu and Mirchandani studied the attributes of information affecting evacuation route choice and demonstrated how to use information to influence evacuees' route choice to reach the SO state (6). Furthermore, disasterand evacuation-related information available through various information dissemination channels to both evacuees and nonevacuees can affect their decisions before and during the evacuation. For example, information about the blockage or closure of a certain area would result in the diversion of nonevacuees who originally intend to traverse the (now-closed) hot zone. Nonevacuees are also likely to synthesize the closure information and past experience to determine their own best alternative route. Such critical aspects of information have not been well addressed in the literature for no-notice evacuation scenarios.The main technical contributions of this study are twofold. First, a simulation-optimization framework is proposed in which a universal quickest flow (UQF)-also known as the earliest arrival flow Modeling of Evacuation and Background Traffic for Optimal Zone-Based Vehicle Evacuatio...

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“…Fleischer [12] gives a faster algorithm for solving the quickest transshipment problem with zero transit times. Mamanda et al [30] give a faster algorithm for tree networks.…”

Section: Introduction and Related Workmentioning

confidence: 99%

Fast and Memory-Efficient Algorithms for Evacuation Problems

Schlöter¹,

Skutella²

2017

Proceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete Algorithms

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We study two classical flow over time problems that capture the essence of evacuation planning. Given a network with capacities and transit times on the arcs and sources/sinks with supplies/demands, a quickest transshipment sends the supplies from the sources to meet the demands at the sinks as quickly as possible. In a 1995 landmark paper, Hoppe and Tardos describe the first strongly polynomial time algorithm solving the quickest transshipment problem. Their algorithm relies on repeatedly calling an oracle for parametric submodular function minimization.We present a somewhat simpler and more efficient algorithm for the quickest transshipment problem. Our algorithm (i) relies on only one parametric submodular function minimization and, as a consequence, has considerably improved running time, (ii) uses not only the solution of a submodular function minimization but actually exploits the underlying algorithmic approach to determine a quickest transshipment as a convex combination of simple lex-max flows over time, and (iii) in this way determines a structurally easier solution in the form of a generalized temporally repeated flow.Our second main result is an entirely novel algorithm for computing earliest arrival transshipments, which feature a particularly desirable property in the context of evacuation planning. An earliest arrival transshipment -which in general only exists in networks with a single sink -is a quickest transshipment maximizing the amount of flow which has reached the sink for every point in time simultaneously. In contrast to previous approaches, our algorithm solely works on the given network and, as a consequence, requires only polynomial space.

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Faster Algorithms for the Quickest Transshipment Problem

Cited by 62 publications

References 23 publications

Optimal Traffic Planning for Efficient Evacuation

Optimal Traffic Planning for Efficient Evacuation

Modeling of Evacuation and Background Traffic for Optimal Zone-Based Vehicle Evacuation Strategy

Fast and Memory-Efficient Algorithms for Evacuation Problems

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