Accelerating DNA Computing via PLP-qPCR Answer Read out to Solve Traveling Salesman Problems

An asymmetric, fully-connected 8-city traveling salesman problem (TSP) was solved by DNA computing using the ordered node pair abundance (ONPA) approach through the use of pair ligation probe quantitative real time polymerase chain reaction (PLP-qPCR). The validity of using ONPA to derive the optimal answer was confirmed by in silico computing using a reverse-engineering method to reconstruct the complete tours in the feasible answer set from the measured ONPA. The high specificity of the sequence-tagged hybridization, and ligation that results from the use of PLPs significantly increased the accuracy of answer determination in DNA computing. When combined with the high throughput efficiency of qPCR, the time required to identify the optimal answer to the TSP was reduced from days to 25 min

A multi-scale framework for fuel station location: from highways to street intersections

Electric drive vehicles (plug-in electric vehicle or hydrogen fuel cell vehicles) have been promoted by governments to foster a more sustainable transportation future. Wider adoption of these vehicles, however, depends on the availability of a convenient and reliable refueling/recharging infrastructure. This paper introduces a path-based, multi-scale, scenario-planning modeling framework for locating a system of alternative-fuel stations. The approach builds on (1) the Flow Refueling Location Model (FRLM), which assumes that drivers stop along their origin-destination routes to refuel, and checks explicitly whether round trips can be completed without running out of fuel, and (2) the Freeway Traffic Capture Method (FTCM), which assesses the degree to which drivers can conveniently reach sites on the local street network near freeway intersections. This paper extends the FTCM to handle cases involving clusters of nearby freeway intersections, which is a limitation of its previous specification. Then, the cluster-based FTCM (CFTCM) is integrated with the FRLM and the DFRLM (FRLM with Deviations) to better conduct detailed geographic optimization of this multi-scale location planning problem. The main contribution of this research is the introduction of a framework that combines multi-scale planning methods to more effectively inform the early development stage of hydrogen refueling infrastructure planning. The proposed multi-scale modeling framework is applied to the Hartford, Connecticut region, which is one of the next areas targeted for fuel-cell vehicle (FCV) market and infrastructure expansion in the United States. This method is generalizable to other regions or other types of fast-fueling alternative fuel vehicles

A location-allocation model of classical central place theory for uniform and non-uniform networks

Thesis (Ph.D.)--Boston UniversityPLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at [email protected]. Thank you.This dissertation presents a location-allocation model of classical (Losch and Christaller) central place theory which is applied to uniform and non-uniform networks. A mixed-integer programming model is developed that incorporates the concepts of range, threshold, distance-elastic demand, and hierarchical nesting.2031-01-0

Hedonic Modeling of Commercial Property Values: Distance Decay from the Links and Nodes of Rail and Highway Infrastructure

This study investigates the impacts of positive and negative externalities of highways and light rail on commercial property values in Phoenix, Arizona. We hypothesize that the positive externality (i.e., accessibility) of highway and light rail accrues at exits and stations, whereas nodes and links of highways and light rail emanate negative effects. Positive and negative effects decay with increasing distance and are captured by multiple distance bands. Hypotheses are tested using a spatial error regression model. Results show that commercial property values are positively and significantly associated with the accessibility benefits of transport nodes. The distance-band coefficients form a typical distance decay curve for both modes with no detectable disamenity donut effect immediately around the nodes. Unexpectedly, impacts of light rail stations extend farther than those of highway exits. Only the links of light rail are negatively associated with property values, as hypothesized. When the sample is subdivided by type of commercial property, the magnitude and distance extent of impacts are surprisingly consistent, with light rail stations having stronger impacts than highway exits on all three classes of commercial property: industrial, office, and retail and service. Rail links have a significant negative relationship with price for all three types of commercial property, but highways have a significant negative relationship only with industrial properties

Evaluating light rail sketch planning: actual versus predicted station boardings in Phoenix

In recent years, transit planners are increasingly turning to simpler, faster, and more spatially detailed “sketch planning” or “direct demand” models for forecasting rail transit boardings. Planners use these models for preliminary review of corridors and analysis of station-area effects, instead of or prior to four-step regional travel demand models. This paper uses a sketch-planning model based on a multiple regression originally fitted to light-rail ridership data for 268 stations in nine U.S. cities, and applies it predictively to the Phoenix, Arizona light-rail starter line that opened in December, 2008. The independent variables in the regression model include station-specific trip generation and intermodal–access variables as well as system-wide variables measuring network structure, climate, and metropolitan-area factors. Here we compare the predictions we made before and after construction began to pre-construction Valley Metro Rail predictions and to the actual boardings data for the system’s first 6 months of operations. Depending on the assumed number of bus lines at each station, the predicted total weekday ridership ranged from 24,767 to 37,907 compared with the average of 33,698 for the first 6 months, while the correlation of predicted and observed station boardings ranged from r = 0.33 to 0.47. Sports venues, universities, end-of-line stations, and the number of bus lines serving each station appear to account for the major over- and under-predictions at the station level

Location of Alternative-Fuel Stations Using the Flow-Refueling Location Model and Dispersion of Candidate Sites on Arcs

The Flow Refueling Location Model (FRLM) is a flow-intercepting model that locates p stations on a network to maximize the refueling of origin–destination flows. Because of the limited driving range of vehicles, network vertices do not constitute a finite dominating set. This paper extends the FRLM by adding candidate sites along arcs using three methods. The first identifies arc segments where a single facility could refuel a path that would otherwise require two facilities at vertices to refuel it. The other methods use the Added-Node Dispersion Problem (ANDP) to disperse candidate sites along arcs by minimax and maximin methods. While none of the methods generate a finite dominating set, results show that adding ANDP sites produces better solutions than mid-path segments or vertices only. Copyright Springer Science+Business Media, LLC 2007Continuous location, Link, Flow intercepting, Hydrogen refueling, Finite dominating set, Vehicle range,