Maximum Travel Time Research Articles

A comparative analysis of two methodologies to estimate well protection zones for transport of viruses from septic tanks in volcanic aquifers in Costa Rica

High groundwater demand in the Great Metropolitan Area (GMA) of Costa Rica, combined with the presence of many septic systems, imposes the necessity to define adequate dimensions for setback distances or protection zones around wellheads to prevent contamination of aquifers by pathogenic organisms. Numerical 3-D simulations of transport of viruses under natural hydrogeological conditions of the northwest section of GMA were performed, considering both porous and fractured porous media with variable saturation. Based on the sensitivity analysis, principal transport parameters for the conditions in the study area are injection concentration, hydraulic conductivity, inactivation rate and attachment rate. Furthermore, a comparative analysis of the arrival of viruses to the water table and the modeling domain’s boundary was carried out using two approaches: maximum permissible concentration criteria and travel time criteria (TT) of 100 days frequently applied in Costa Rica for fractured rocks aquifers. The analysis indicates that under conditions of low mobility and high removal rates (typical for soils of volcanic origin), the TT approach overestimates the dimension of the protection zone. On the other hand, when conditions of high mobility and low removal rate are considered, the TT approach usually underestimates that dimension. It is recommended to perform more field and laboratory studies to obtain better representative parameters for soils of volcanic origin.

Siting of HIV/AIDS diagnostic equipment in South Africa: a case study in locational analysis

AbstractThis paper describes a practical application of locational analysis to the siting of HIV/AIDS diagnostic equipment in laboratories across South Africa. Classical location analytical techniques were extended to ensure that laboratories are sited as close as possible to major centers of demand from hospitals and clinics. A particular advantage of the modified set covering algorithm developed is that choices between laboratory sites are made in a transparent manner. In order to find appropriate numbers and ideal placement of CD4 laboratories, runs were undertaken for various scenarios based on maximum travel time from health facilities to laboratory sites. Results demonstrated to decision makers showed close comparisons with pilot review projects undertaken in four health districts of South Africa. The research has potential to impact health‐care delivery to HIV sufferers in the poorest rural regions of the country.

Field implementation feasibility study of cumulative travel‐time responsive (CTR) traffic signal control algorithm

SummaryThe cumulative travel‐time responsive (CTR) algorithm determines optimal green split for the next time interval by identifying the maximum cumulative travel time (CTT) estimated under the connected vehicle environment. This paper enhanced the CTR algorithm and evaluated its performance to verify a feasibility of field implementation in a near future. Standard Kalman filter (SKF) and adaptive Kalman filter (AKF) were applied to estimate CTT for each phase in the CTR algorithm. In addition, traffic demand, market penetration rate (MPR), and data availability were considered to evaluate the CTR algorithm's performance. An intersection in the Northern Virginia connected vehicle test bed is selected for a case study and evaluated within vissim and hardware in the loop simulations. As expected, the CTR algorithm's performance depends on MPR because the information collected from connected vehicle is a key enabling factor of the CTR algorithm. However, this paper found that the MPR requirement of the CTR algorithm could be addressed (i) when the data are collected from both connected vehicle and the infrastructure sensors and (ii) when the AKF is adopted. The minimum required MPRs to outperform the actuated traffic signal control were empirically found for each prediction technique (i.e., 30% for the SKF and 20% for the AKF) and data availability. Even without the infrastructure sensors, the CTR algorithm could be implemented at an intersection with high traffic demand and 50–60% MPR. The findings of this study are expected to contribute to the field implementation of the CTR algorithm to improve the traffic network performance. Copyright © 2017 John Wiley & Sons, Ltd.

Normal moveout for long offset in isotropic media using the Padé approximation

The normal moveout correction is important to long-offset observations, especially deep layers. For isotropic media, the conventional two-term approximation of the normal moveout function assumes a small offset-to-depth ratio and thus fails at large offset-to-depth ratios. We approximate the long-offset moveout using the Pade approximation. This method is superior to typical methods and flattens the seismic gathers over a wide range of offsets in multilayered media. For a four-layer model, traditional methods show traveltime errors of about 5 ms for offset-to-depth ratio of 2 and greater than 10 ms for offset-to-depth ratio of 3; in contrast, the maximum traveltime error for the [3, 3]-order Pade approximation is no more than 5 ms at offset-to-depth ratio of 3. For the Cooper Basin model, the maximum offset-to-depth ratio for the [3, 3]-order Pade approximation is typically double of those in typical methods. The [7, 7]-order Pade approximation performs better than the [3, 3]-order Pade approximation.

Planning and optimization of intermodal hub-and-spoke network under mixed uncertainty

This paper addresses the planning and optimization of intermodal hub-and-spoke (IH&S) network considering mixed uncertainties in both transportation cost and travel time. Different from previous studies, this paper develops a novel modeling framework for the IH&S network design problem to jointly minimize the expected value of total transportation costs and the maximum travel time requirement in term of critical value. A new hybrid methodology by combining fuzzy random simulation (FRS) technique and multi-start simulated annealing (MSA) algorithm is designed to solve the proposed model. Numerical experiments are implemented to verify the effectiveness of the proposed model and solution approach.

The traveling salesman problem with pickup, delivery, and ride-time constraints

In the traveling salesman problem with pickup, delivery, and ride-time constraints (TSPPD-RT), a vehicle located at a depot is required to service a number of requests where the requests are known before the route is formed. Each request consists of (i) a pickup location (origin), (ii) a delivery location (destination), and (iii) a maximum allowable travel time from the origin to the destination (maximum ride-time). The problem is to design a tour for the vehicle that (i) starts and ends at the depot, (ii) services all requests, (iii) ensures that each request's ride-time does not exceed its maximum ride-time, and (iv) minimizes the total travel time required by the vehicle to service all requests (objective function). A capacity constraint that may be present is that the weight or volume of the undelivered requests on the vehicle must always be no greater than the vehicle's capacity. In this article, we concurrently analyze the TSPPD-RT with capacity constraints and without capacity constraints. We describe two mathematical formulations of the problem. These formulations are used to derive new lower bounds on the solution to the problem. Then, we provide two exact methods for finding the optimal route that minimizes the total travel cost. Our extensive computational analysis on both versions of the TSPPD-RT shows that the proposed algorithms are capable of solving to optimality instances involving up to 50 requests. © 2015 Wiley Periodicals, Inc. NETWORKS, Vol. 67(2), 95–110 2016

Analytical Derivation of Overland Travel Time Based on Diffusive Wave Solution

AbstractDerivation of spatial distribution of travel time is required in some conceptual rainfall-runoff transformation models. Application of a kinematic wave (KW) solution to delineate isochrones of travel time may be straightforward, particularly in an overland flow regime. In this article, a new analytical approach based on the diffusive wave (DW) solution is developed for calculation of travel time. The discharge hydrograph over a rectangular plane will be calculated based on the developed analytical DW method through the application of the time-area method. Differences between calculated maximum travel time (i.e., equilibrium time), isochrone locations, and outflow discharge between the KW and DW solutions are compared with those of the numerical dynamic wave (DYW) solution. It is shown that analytical DW results are closer to those of the DYW in comparison with those of the KW. The effect of the K0F02 number on the solution accuracy is investigated, where K0 is the kinematic wave number and F0 is t...

A hybrid column generation and clustering approach to the school bus routing problem with time windows

<span>This paper attempts to solve the School Bus Routing Problem with Time Windows that consists of finding the best set of routes to pick up students distributed geographically with constraints as capacity, time windows and maximum travel time. We formulated the problem as a classic Vehicle Routing Problem with Time Windows and solved it using an approach based on a clustering algorithm and column generation method. A real world case from a school in Bogotá, Colombiais presented including 600 students to pick up in near 400 nodes located in urban and rural areas. The obtained results demonstrate a reduction as the problem’s complexity and an improvement on the performance measures of the proposed method.</span>

Abstract A75: Racial and ethnic differences in travel time to mammography facilities in 5 US cities

Abstract Introduction: Screening by mammography is one component of an overall strategy to identify early breast cancer and reduce breast cancer mortality. While women in rural areas may be at a disadvantage in accessing mammography, urban residents who depend on public transportation can also face barriers to mammography services, despite generally shorter travel distances. We examined travel time using public transportation from census tracts to mammography facilities in Boston, Philadelphia, San Antonio, San Diego and Seattle. Methods: Data sources included: U.S. 2010 census data used to identify women 40 years of age and older, and race/ethnicity groups by census tract in each city; American Community Survey data to determine household availability of a private vehicle; NAVTEQ street network for each metropolitan area; and FDA's certification and inspection records of U.S. mammography facilities. Using the public transportation option on Google Trip Planner we obtained the travel time from the centroid of each census tract to the nearest mammography facility. A standard trip time of 11:00 am on weekdays was used for all searches. We calculated tract percentages of households with no vehicle availability and percentage blacks, whites, Asians and Hispanics for each metropolitan area. Median travel times were obtained by summing travel time by vehicle access and race/ethnicity across all census tracts in the metropolitan area. Finally, we calculated overall mammography capacity ratios (number of machines * estimated number of mammograms per machine / population of women 40 years of age and older) for each city. Results: Overall, median travel times to the closest mammography facilities by public transportation were 21 minutes in Philadelphia, 27 minutes in Boston, 33 minutes in Seattle, 34 minutes in San Antonio, and 35 minutes in San Diego. Across all cities, travel time increased as availability of a private vehicle increased indicating a suburban effect. Focusing on census tracts with low private vehicle availability we saw little differences in median travel time by race/ethnicity in Philadelphia (13 to 14 minutes) and Boston (14 to 15 minutes) while in Seattle, whites had the shortest travel time (23 minutes) compared to blacks, Asians, and Hispanics (30 minutes). In San Antonio and San Diego, blacks had the longest travel times (33 minutes and 28 minutes) compared to the other groups. Maximum travel times in tracts with low vehicle availability ranged from 86 minutes to over two hours. There was less variability in travel times for census tracts classified as having high vehicle availability. Conclusion: Our results reveal a geographic pattern of wide-ranging travel times within and across the five metropolitan areas with regard to low-vehicle-availability populations. The Eastern cities of Boston and Philadelphia, with well-developed train systems, had travel times to the nearest mammography facility that were almost 10 to 15 minutes (21% to 39%) shorter than the western cities of San Diego, San Antonio and Seattle. Across all metropolitan areas in the low vehicle availability category, white census tracts tended to have among the shortest travel times. In the Western cities only black census tracts consistently had longer travel times than whites while Hispanic and Asian travel times varied relative to that of whites. Although mammography capacity was adequate at the metropolitan level, we found maximum travel times of more than two hours for residents of some census tracts having low private vehicle availability. Citation Format: Shannon Graham, Brian Lewis, Barry Flanagan, Meg Watson, Lucy Peipins. Racial and ethnic differences in travel time to mammography facilities in 5 US cities. [abstract]. In: Proceedings of the Sixth AACR Conference: The Science of Cancer Health Disparities; Dec 6–9, 2013; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2014;23(11 Suppl):Abstract nr A75. doi:10.1158/1538-7755.DISP13-A75

Heuristic Algorithms for Solving an Integrated Dynamic Center Facility Location - Network Design Model

This paper studies the problem of determining optimal facility location and network design decisions over multiple time periods considering equity-based objective. The problem determines optimal locations of facilities and the design of the underlying network, taking into account budget constraints on opening facilities and constructing links for each time period during the planning horizon. The objective is to minimize the sum over all time periods of the maximum travel time between nodes and facilities for each time period. We propose a mixed-integer, non-linear programming model to address the problem. The non-linear terms of the model relevant to the objective function can be easily converted to linear terms. Due to the high complexity of the model, CPLEX could not solve the problem efficiently. Hence, we propose two heuristics based on linear relaxation and a hybrid algorithm based on Variable Neighborhood Search to solve the problem. We tested the performance of the proposed algorithms on two data sets with up to 60 nodes, 708 candidate links, and 20 time periods compared to each other and the CPLEX solver.

Two new models for redeployment of ambulances

Nowadays, in all countries, public resources for healthcare are inadequate to meet the demands for the services. Therefore, policy makers should provide the most effective healthcare services to citizens within the limited available resources. During the past decades, lots of research using operations research techniques, tools, and theories has been applied to a wide range of problems in healthcare. Ambulance service planning is a branch of healthcare. Ambulance location and redeployment problems are considered two important issues in ambulance service planning. In these models, an attempt is made to maximize coverage in the districts and properly service the patients in emergency situations.In this paper, at first we use an existing model, named MECRP1Maximal Expected Coverage Relocation Problem.1, to locate ambulances in four districts of Isfahan, Iran. Then, we formulate a generalized assignment model with the aim of minimizing the total time traveled by ambulances. We also formulate a generalized bottleneck assignment model. The goal of this model is to minimize the maximum travel time. The proposed models specify the movement of the ambulances, using the out of MECRP determines the relocation of the ambulances in just one run for all possible combinations. In fact, each of these models specifies the movement of the ambulances from hospitals to stations or from stations to other stations based on its aim.In addition, to shed light on the merits of the proposed models, computational results on experimental data from Isfahan EMS agency are provided. The results, using these models, show travel times can be significantly reduced. By the end of this paper, the corresponding conclusions are expressed.

Optimization of a feeder-bus route design by using a multiobjective programming approach

This paper presents a feeder-bus route design model, capable of minimizing route length, minimizing maximum route travel time of planned routes, and maximizing service coverage for trip generation. The proposed model considers constraints of route connectivity, subtour prevention, travel time upper bound of a route, relationships between route layout and service coverage, and value ranges of decision variables. Parameter uncertainties are dealt with using fuzzy numbers, and the model is developed as a multiobjective programming problem. A case study of a metro station in Taichung City, Taiwan is then conducted. Next, the programming problem in the case study is solved, based on the technique for order preference by similarity to ideal solution approach to obtain the compromise route design. Results of the case study confirm that the routes of the proposed model perform better than existing routes in terms of network length and service coverage. Additionally, increasing the number of feeder-bus routes decreases maximum route travel time, increases service coverage, and increases network length. To our knowledge, the proposed model is the first bus route design model in the literature to consider simultaneously various stakeholder needs and support for bus route planners in developing alternatives for further evaluation efficiently and systematically.

Urban goods movements in a sensitive context: The case of Parma

This paper focuses on the efficiency of one-to-many distribution processes in urban environments. An in-depth 8-month survey of commercial vehicle tours leaving from an Urban Distribution Centre (UDC) located on the outskirts of the city of Parma (Italy), was carried out, merging information from a GPS-based dataset and a wider operation dataset. Tours were classified according to UDC–customer distances in order to prove the clear correlation between the efficiency of the distribution process and the size (and the network characteristics) of the area being served. When such area covers the city center, available data highlighted how vehicle routing is affected by constraints which strongly prevent the optimization of routes and occupancy rate.Through continuous approximation models, the relative impact of the time-dependent parameters of the delivery process, particularly maximum tour travel times and preferred time slots for deliveries, was analyzed along with the effects of traffic congestion on commercial vehicle tours. The resulting scenario analysis allowed to assess a significant increase in the number of tours needed (+34,3%) and the total distance travelled (+9%), to serve a given set of customers in the city center, when travel time variability and tour duration constraint become stricter.

Travel time and distances to Norwegian out-of-hours casualty clinics

Geographical factors have an impact on the utilisation of out-of-hours services. In this study we have investigated the travel distance to out-of-hours casualty clinics in Norwegian municipalities in 2011 and the number of municipalities covered by the proposed recommendations for secondary on-call arrangements due to long distances. We estimated the average maximum travel times and distances in Norwegian municipalities using a postcode-based method. Separate analyses were performed for municipalities with a single, permanently located casualty clinic. Altogether 417 out of 430 municipalities were included. We present the median value of the maximum travel times and distances for the included municipalities. The median maximum average travel distance for the municipalities was 19 km. The median maximum average travel time was 22 minutes. In 40 of the municipalities (10 %) the median maximum average travel time exceeded 60 minutes, and in 97 municipalities (23 %) the median maximum average travel time exceeded 40 minutes. The population of these groups comprised 2 % and 5 % of the country's total population respectively. For municipalities with permanent emergency facilities(N = 316), the median average flight time 16 minutes and median average distance 13 km.. In many municipalities, the inhabitants have a long average journey to out-of-hours emergency health services, but seen as a whole, the inhabitants of these municipalities account for a very small proportion of the Norwegian population. The results indicate that the proposed recommendations for secondary on-call duty based on long distances apply to only a small number of inhabitants. The recommendations should therefore be adjusted and reformulated to become more relevant.

The use of space–time constraints for the selection of discretionary activity locations

The development of methods of studying individuals’ selection of discretionary activity locations remains a challenge for empirical analysts and transport modelers. Time geography and, in particular, the concept of space–time constraints provides a useful framework for these selection processes. In this work we empirically determine space–time constraints from the Chilean household and travel survey. Based on a specific activity pattern example, where trips are made from home to work to a discretionary activity and back home, we estimate detour factors. Detour factors describe the spatial deviations that are made from the home-work axis to conduct the discretionary activity. Using GIS we estimate potential path areas (PPAs), where discretionary activities may be located. Within the PPAs, applying a time constraint that is the maximum daily travel time refines the selection of discretionary activity locations. The thresholds of the daily travel time vary according to the PPA-size and mode combinations. We were able to reproduce between 38% and 72% of the discretionary location choices observed in the survey (according to the rigor of the constraints applied).

The effect of inhomogeneous water on seismic imaging in deepwater areas of the South China Sea

This paper examines the effect of inhomogeneous water on seismic imaging in deep water areas. An appropriate partial differential equation is derived for the acoustic pressure field in inhomogeneous water, including current effects. Seismic wavefields are simulated and the results show that the traveltime of seismic waves can be affected. The maximum traveltime perturbation at zero offset is 20 ms. In particular, the structure of horizontal reflectors below the water is distorted by mesoscale eddies. Variations of water temperature are the fundamental cause of the distortion. Finally, a calibration method for the distortion of seismic imaging caused by inhomogeneous water is presented.

An orienteering model for the search and rescue problem

In this paper, we propose a new model for the search and rescue problem. We focus on the case of a single airborne search asset through a connected space and continuous time with a maximum travel time $$T$$ . The intent is to maximize the detection of a cooperative target (search and rescue). The proposed model is based on the assumption of existing a priori information (e.g., result of information fusion process) to establish a spatial distribution of probability of containment in possible geographic locations. The possibility area is defined using a cut threshold on the probability of containment and the search path as well as the allocation of the level of effort to each region in the search space is obtained based on an orienteering model. We illustrate the application of the proposed model on an empirical example.

Experimental Study of Effects of Travel Time Distribution Information on Dynamic Route Choice Behavior

This study focuses on the possibility that providing travelers with information on travel time distribution, along with the existing travel time information, might affect their decision making and enhance traffic control. As an initial step to confirm the effectiveness of travel time distribution information, we use a laboratory experiment to obtain panel data of route choices when information is provided. The rationality of the behavior of the respondents and the characteristics of the route choice are first analyzed by aggregation analysis and then statistically examined by specifying a mixed logit route choice model. As a result, it is revealed that both travel time information and maximum travel time information significantly affect route choice behavior when a penalty is imposed for late arrival.

A Multi-objective Imperialist Competitive Algorithm for a Capacitated Single-allocation Hub Location Problem

In this paper, we present a novel multi-objective mathematical model for capacitated single allocation hub location problem. There are the vehicle capacity constraint and capacity restrictions amount of the incoming flow to the hub while the balancing requirements of incoming quantities of flow to the each hub is considered. Moreover, there is a set of available capacities for each potential hub, among which one can be chosen. The multiple objectives are to minimize total cost of the networks regarding minimizing maximum travel time between nodes. Due to NP-Hard property of our problem, this model is solved by a multi-objective imperialist competitive algorithm (MOICA) and finally, to prove its efficiency, the related results are compared with the results obtained by the well-known multi-objective evolutionary algorithm, called NSGA-II. The associated results confirm the efficiency and the effectiveness of our proposed MOICA to provide good solutions, especially for medium and large-sized problems.

Multi-Criteria Covering-Based Location of Volunteer Fire Departments

In Germany, a large number of volunteer fire departments (VFD) exist that have been founded in order to provide regional support for professional firefighters. The current locations of these volunteer fire departments might be suboptimal with respect to costs and availability. Due to historical developments the city of Bochum (Germany) also hosts a large number of volunteer fire departments. A mixed-integer linear program is presented in order to investigate the consequences of partial relocating or closing of volunteer fire departments. Timeliness is one of the most important objectives since it reflects the quality of emergency services such as firefighting systems. Timeliness means that in most instances the emergency can be reached within a predefined time limit after reception of the emergency call. A sufficient number of firefighting facilities have to be established and located in order to provide high quality services over a wide area with spatially distributed demands. Different criteria are taken into account in order to find optimal locations. Minimizing the average travel time and minimizing the maximum travel time are goals which are in conflict with minimizing costs for establishing facilities and for transport. A multi-criteria approach is applied and different solutions for an urban area with several volunteer firefighting departments are analyzed. The tradeoff between maximizing the quality of emergency services and cost reduction is illustrated using a real world case study with 18 existing volunteer fire departments.