142 research outputs found
Emergency Medical Service System Design Evaluator
No full textEffectiveness of emergency medical services (EMS) depends on a wide range of decisions in its planning and operation phase such as ambulance locations and dispatching protocols. Much research has been conducted on EMS design and operational decision making in order to improve the quality of EMS systems. It is often the case that these research works focus on a decision problem on a specific aspect and tend to overlook possible interactions from other elements of an EMS system. This paper introduces a simulation model as a generic EMS system design evaluator, where a wide range of design and operational factors are comprehensively incorporated. Experiments using the developed model show that there exist interactions among many design and operational factors in an EMS system, which demonstrates the importance of considering all decisions when developing solutions for a specific decision problem in EMS design and operation
MSC790775 Supplemental material - Supplemental material for Estimating age group-dependent sensitivity and mean sojourn time in colorectal cancer screening
No full textSupplemental material, MSC790775 Supplemental material for Estimating age group-dependent sensitivity and mean sojourn time in colorectal cancer screening by Na Young Sung, Jae Kwan Jun, Youn Nam Kim, Inkyung Jung, Sohee Park, Gyu Ri Kim and Chung Mo Nam in Journal of Medical Screening</p
Problem Instances for the Generalized Assignment Problem (GAP) with Resource-Independent Task Profits and Identical Resource Capacity
No full textThis dataset includes the problem instances generated for the Generalized Assignment Problem (GAP) with resource-independent task profits and identical resource capacity.
We have set the four problem features - the number of tasks, the number of resources, the homogeneity of resources, and the relative capacity ratio of resources to total demands for tasks - with different levels for the features, resulting in 54 classes of the problem instances. For each class, 20 instances are generated, thus, a total of 1080 instances is included in the dataset.
The main aim for this dataset creation was to test the performance of a solution algorithm to the target optimization problem and to characterize the performance of the algorithm as a function of the problem feature values. The findings along with the process could help a solution algorithm developer to understand the target optimization problem and thus design a solution algorithm with acceptable performance
Realization of a Strained Atomic Wire Superlattice
No full textA superlattice of strained Au-Si atomic wires is successfully fabricated on a Si surface. Au atoms are known to incorporate into the stepped Si(111) surface to form a Au-Si atomic wire array with both one-dimensional (1D) metallic and antiferromagnetic atomic chains. At a reduced density of Au, we find a regular array of Au-Si wires in alternation with pristine Si nanoterraces. Pristine Si nanoterraces impose a strain on the neighboring Au-Si wires, which modifies both the band structure of metallic chains and the magnetic property of spin chains. This is an ultimate 1D version of a strained-layer superlattice of semiconductors, defining a direction toward the fine engineering of self-assembled atomic-scale wires. © 2015 American Chemical Society1771sciescopu
Travel Time and Fuel Consumption Optimization in Vehicle Routing under Fuzzy Congestion: A study of dynamic traffic routing with congestion levels calculated by applying fuzzy logic
No full textIn research, there is increasing interests in both efficient vehicle routing and quantified definitions of traffic congestion. As congestion can have a significant impact on most common routing parameters, especially travel time and fuel consumption, it could be beneficial to incorporate the traffic congestion into vehicle routing. As such, we define a fuzzy inference system to determine the level of congestion from the average speed and traffic density on a given road segment. The traffic congestion is then used to define penalties applied to the objective parameter in a Dijkstra's algorithm. The objective parameter to be minimized will be either fuel consumption or travel time, both described by a function of speed. The use of weighted moving average to forecast the input values of the routing is also investigated. The tests indicates that utilizing fuzzy determined traffic congestion can indeed improve the accuracy of routing algorithms, though when it comes to forecasting, there might be better options than the weighted moving average
Winter Gritting Routes with Multiple Visits: A heuristic for a capacitated arc routing problem with heterogenous vehicles with different covering widths.
No full textI dette projekt adresserer vi de praktiske aspekter af at løse problemet man står overfor når man skal planlægge ruter til saltspredning. Dette gør vi som et Capacitated Arc Routing Problem (CARP). Specifikt og baseret på samtaler med COWI og en gennemgang af den relevante litteratur, finder vi to primære mangler i den nuværende litteratur. Vi udvælger den vigtigste af disse som fokus for rapporten. Det er problemet med at antallet af gange et saltspredningskøretøj skal besøge et stykke vej for at servicere det afhænger det specifikke køretøj. Vi foreslå derefter en løsnings heuristik som kan håndtere denne type problem, altså bestemme hvilke veje der skal serviceres af hvilke køretøjer. Den foreslåede løsning gør brug af eksisterende metoder til de underproblemer der er velbeskrevne i litteraturen og introducere samtidig en måde at håndtere de potentielt flere besøg. Vi tuner løsningens parametre og tester den på noget test data fra litteraturen. Vi finder ud af at løsningen fungerer, og selvom der ikke eksisterer andre løsninger vi kan sammenligne vores resultater med så finder vi potentiale for yderligere forbedringer hvilket vi adresserer til sidst.In this project we address the practical aspects of solving the problem of winter gritting, as a Capacitated Arc Routing Problem (CARP). Specifically, based on discussions with COWI, and a literature review we find two main gaps in the current literature, and focus on the most important of these. That is the fact that the number of times a vehicle needs to visit a road to service it depends on the specific vehicle. We then proceed to propose a solution heuristic which can handle this type of problem, i.e. determining which roads should be serviced by which vehicles. The proposed solution utilizes existing methods for the sub-problems that are well researched, while introducing a method for the multiple visits. The parameters of the proposed solution are tuned and we test our heuristic on test instances from literature. We find that the proposed solution works and while there are no existing solutions in the literature to compare our results to, we find potential for improvement which we address at the end
Safe Path Planning Under Uncertainty
No full textDette speciale undersøger, hvorledes en rute plan for en UAV kan laves - når der er områder, som det ønskes at UAVen holder afstand fra, da disse områder er forbundet med en risiko. Specialet tager udgangspunkt i en introduktion af de forskellige metoder og setups der er brugt i andre sammenhænge til at beskrive lignende problemer. Derefter udvides der med en problemstilling og beskrivelse af, hvordan det håndteres at der kan være usikkerhed iforhold til områderne der skal holdes afstand fra, dette giver forskellige scenarier at se ind i. Regionen som UAVen skal igennem fremsættes som en grid baseret graf, hvorved en risiko minimerende rute kan findes gennem grafen ved anvendelse af dynamic programming with resource constraint. Den anvendte algoritme ændres også således at det er muligt at se ind i flere scenarier og finde en robust løsning. Tilsidst evalueres setuppet igennem en sensitivitetsanalyse
Zoning under Environmental Uncertainty: With Applications for Autonomous Vehicle Routing
No full textWith the increasing size of wildfires (NationalInteragency Fire Center [21]) a need for effec-tive ways of monitoring and containing thefires spread has emerged. The use of un-manned aerial vehicles (UAVs) for optical mon-itoring of a spreading wildfire is appropriatedue to e.g., the longevity of missions and thehazardous environment.With the increasing size of fires more UAVsare needed to effectively monitor an area, lead-ing to more potential conflicts between UAVs,thereby requiring the need for communicationif a UAV were to deviate from its plannedroute. However there are many situationswhere communication between UAVs is notpractical or even impossible. This project there-fore explores zoning methods that will alloweach agent to have navigational freedom whilenot needing to communicate in order to avoidconflicts.This problem is formulated as a 2-stagestochastic linear programming problem, thatreflects the zoning and flight stage, wherethe environmental uncertainty during flightshould be considered when constructing zones.This is solved using two zoning methods, in-spired by the literature (Khemakhem et al.[18]) as well as a novel routing-based cluster-ing method proposed by the authors. These arethen compared using cumulative route scoresfor routes generated in the resulting zones.Their applicability for dynamic environmentsis further tested by considering how often eachof the zoning solutions routes can be optimallyupdated while respecting zone boundaries.Lastly, the aforementioned zoning methods arecompared with a traditional routing approach,in order to gauge performance degradationdue to zone restrictio
Three-Dimensional Surface Area Computation and Coverage Optimization in Directional Sensor Networks: With Applications for Vertical Farming
No full textIn an increasingly automated society monitoring becomes more and more important. Especially in production lines sensors play a vital role in ensuring quality and uniformity in products. A broad range of sensors are being employed to handle the task. In this paper we examine a selection of directional sensors in a vertical farm setting. By use of a Particle Swarm Optimization algorithm we try to maximize the surface area covered by a sensor in a bounded environment. It is possible for the algorithm to improve upon an initial, randomly generated position of the sensor and find a near optimal solution with maximized surface area covered. Additionally, we find that static sensors are being outperformed significantly by sensors with gyral capabilities
Traffic Light Control Using Deep Reinforcement Learning At An Isolated Intersection With Pedestrians
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