Optimization Model For Distributed Routing For Disaster Area Logistics

Osman, Mojahid F. Saeed; Ram, Bala; Bhadury, Joyendu; Stanfield, Paul; Davis, Lauren B.; Samanlıoğlu, Funda

doi:10.1109/soli.2009.5203944

Cited by 9 publications

(2 citation statements)

References 23 publications

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“…Multi-commodity flows over time are a useful tool for modelling problems that involve non-instantaneous transportation through some kind of network. Some recent examples for such problems include aircraft routing [1], cloud computing [2,3], road traffic networks [4], disaster management [5,6], evacuations [7], logistics [8,9], packet routing [10] and shared-ride systems [11].…”

Section: Introductionmentioning

confidence: 99%

A tight bound on the speed-up through storage for quickest multi-commodity flows

Groíß

Skutella

2015

Operations Research Letters

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Multi-commodity flows over time exhibit the non-intuitive property that letting flow wait can allow us to send flow faster overall. Fleischer and Skutella (IPCO 2002) show that the speed-up through storage is at most a factor of 2, and that there are instances where the speed-up is as large as a factor of 4/3. We close this gap by presenting a family of instances for which the speed-up factor through storage converges to 2.

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Section: Introductionmentioning

confidence: 99%

A tight bound on the speed-up through storage for quickest multi-commodity flows

Groíß

Skutella

2015

Operations Research Letters

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“…There are two broad aspects in evacuation planning: (1) moving people out of the disaster zone, and (2) moving people and material into the same area (i.e safe shelters and refuge areas) [14]. Kongsomsaksakul et al [15] utilized a bi-level programming problem to model assignment of shelters within disaster zones for evacuees to escape to in times of disaster.…”

Section: Related Workmentioning

confidence: 99%

Discrete Time Dynamic Traffic Assignment Models with Lane Reversals for Evacuation Planning

Poh¹

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In an event of a natural or man-made disaster, an evacuation is likely to be called for to move residents away from potentially hazardous areas. Road congestion and traffic stalling is a common occurrence as residents evacuate towns and cities for safe refuges. Lane reversal, or contra-flow, is a remedy to increase outbound flow capacities from disaster areas which in turn will reduce evacuation time of evacuees during emergency situations. This thesis presents a discrete-time traffic assignment system with lane reversals which incorporates multiple sources and multiple destinations to predict optimal traffic flow at various times throughout the entire planning horizon. With the realization of lane reversals, naturally the threat of potential head-on collisions emerges. To avoid the occurrence of such situations, a collision prevention constraint is introduced to limit directional flow on lanes based on departure time. This model belongs to the class of dynamic traffic assignment (DTA) problems. Initially the model was formulated as a discrete-time system optimum dynamic traffic assignment (DTA-SO) problem, which is a mixed integer nonlinear programming problem. Through various proven theorems, a linearized upper bound was derived that is able to approximate the original problem with very high precision. The result is an upper bound mixed integer linear programming problem (DTA-UB). The discrete-time DTA model is suitable for evacuation planning because the model is able to take care of dynamic demands, and temporal flow assignment. Also, simultaneous route and departure is assumed and an appropriate travel time function is used to approximate the minimum and maximum travel time on an arc. This thesis discusses the different attributes that relates to Dynamic Traffic Assignment. DTA model properties and formulation methodology are also expounded upon. A model analysis that breaks down each output into individual entities is provided to further understand the computational results of small networks. A no reversal DTA-UB model (NRDTA-UB) is formulated and its computational results are compared to DTA-UB. Through the extensive computational results, DTA-UB is proven to obtain much better results than NRDTA-UB despite having longer solving time. This is a step toward realizing the supremacy of having lane reversals in a real-life evacuation scenario.

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