A Type of Transportation Problem to be Solved Following the Time Criterion and Considering Vehicle Features

The formulation of classical minimax transport-type problems involves the search for an optimal transportation plan considering only time of delivery of resources. The inevitable additional costs of processing resources at the origin and destination are usually not considered. This approach is fully justified given incommensurability of delivery times of resources along available routes and times of preliminary/subsequent processing of resources. At the same time, in a number of practical problems, the time spent on loading/unloading (for example, when organizing loading of packaged mineral fertilizers from port warehouses onto ships) can be of significant importance. In such cases, when searching for an optimal transportation plan, it is necessary to take into account not only travel times of vehicles used along the set routes, but also the costs of loading and unloading operations, considering the number of available vehicles and their characteristics, for example, payload.In this regard, the objective of the study is not only to develop a method for calculating the optimal transportation plan, but also a method for distributing vehicles, considering their number and features.At the same time, another no less important objective of the study is to substantiate the application of the method of successive reduction of residuals, considering the form of the objective function, which considers not only the main parameters of classical minimax transport-type problems, but also the quantitative characteristics of vehicles involved in the transport operation. It is fundamentally important that the use of the method of successive reduction of residuals determines the polynomial computational complexity of the algorithm, which makes it possible to use it in the operational solution of problems of practical dimension.To solve the problem of distributing available vehicles according to the origin points, considering payload of vehicles, it is proposed to use the method of dynamic programming. An illustrative example of distribution of delivery vehicles, adapted for the use in MS Excel, is considered.

An equity and efficiency integrated grid-to-level 2SFCA approach: spatial accessibility of multilevel healthcare

Background Equity of healthcare spatial access is essential for the health outcomes of medical investments and the welfare of populations, and efficiency of medical resource allocation is important for obtaining a supply-demand equilibrium with lower cost and higher outputs with limited inputs. However, the literature that involves both equity and efficiency in its analysis of healthcare spatial allocation is rare, and the spatial accessibility of multilevel healthcare is difficult to measure by traditional methods in a large region with diversified population distribution. Methods To assist in solving these issues, this paper aims to build an equity and efficiency integrated analytical framework by proposing a new “GTL-2SFCA” approach to analyze the spatial accessibility of multilevel healthcare; maximum and minimum floating catchments of different levels of healthcare were assigned to ensure a combination of universal search coverage and efficient hospitalization behavior simulation. Results The analytical framework was applied and tested in Hubei, China. Almost half of the residents (47.95%) and townships (44.98%) have access to both public general hospitals (PGHs) and primary healthcare centers (PHCs) services, 36.89% of the residents enjoy only one sufficient service, either PGHs or PHCs, and the remaining residents (15.16%) are faced with the risk of lacking access to both services. The results reveal that there are core-periphery effects of multilevel healthcare throughout Hubei and isolate clusters that have adequate access in the western region. The polarization effect of higher-level healthcare and the polycentric pattern of lower-level healthcare coexist. The multilevel healthcare shortage was identified in some areas in boundary and peripheral regions. Conclusions This study integrates equity and efficiency into the GTL-2SFCA framework, enriches the FCA series methodologies and provides a more operational solution for evaluating the access of residents in more sophisticated spatial units to each level of healthcare. By more significantly differing and quantifying the catchment area and distance decay effect, this methodology avoids overestimating or underestimating accessibility and discovers some imperceptible spatial inequities. This study has application value for researchers and decision-makers in other scenarios and regions with significant heterogeneity in medical resources and where the population has greater mobility.

Dynamic Model of Contingency Flight Crew Planning Extending to Crew Formation

The creation of a flight schedule and the associated crew planning are clearly among the most complicated tasks in terms of traffic preparation. Even with a relatively small number of pilots and aircraft, numerous specific constraints arising from real operations must be included in the calculation, thus increasing the complexity of the planning process. However, even in a precision-planned operation, non-standard situations often occur, which must be addressed flexibly. It is at this point that an operational solution must be applied, the aims of which are to stabilize the flight schedule as soon as possible and minimize the financial impacts resulting from the non-standard situation. These problems are resolved by the airline’s Operational Control Center, which also uses various software approaches to solve the problem. The problem is approached differently by large air carriers, which use software products to address it, and small and medium-sized air carriers, which resolve the issue of operational rescheduling intuitively, based on the experience of dispatchers. However, this intuitive approach can lead to inaccuracies that can lead to unnecessary financial losses. In this paper, we present an optimization model that can serve as a tool to support the decision-making of employees of the operations centers of smaller and medium-sized air carriers.

Expert Knowledge as Basis for Assessing an Automatic Matching Procedure

The continuous development of machine learning procedures and the development of new ways of mapping based on the integration of spatial data from heterogeneous sources have resulted in the automation of many processes associated with cartographic production such as positional accuracy assessment (PAA). The automation of the PAA of spatial data is based on automated matching procedures between corresponding spatial objects (usually building polygons) from two geospatial databases (GDB), which in turn are related to the quantification of the similarity between these objects. Therefore, assessing the capabilities of these automated matching procedures is key to making automation a fully operational solution in PAA processes. The present study has been developed in response to the need to explore the scope of these capabilities by means of a comparison with human capabilities. Thus, using a genetic algorithm (GA) and a group of human experts, two experiments have been carried out: (i) to compare the similarity values between building polygons assigned by both and (ii) to compare the matching procedure developed in both cases. The results obtained showed that the GA—experts agreement was very high, with a mean agreement percentage of 93.3% (for the experiment 1) and 98.8% (for the experiment 2). These results confirm the capability of the machine-based procedures, and specifically of GAs, to carry out matching tasks.

ON THE JOINT EXPLOITATION OF OPTICAL AND SAR SATELLITE IMAGERY FOR GRASSLAND MONITORING

Time series of optical and Synthetic Aperture RADAR (SAR) images provide complementary knowledge about the cover and use of the Earth surface since they exhibit information of distinct physical nature. They have proved to be particularly relevant for monitoring large areas with high temporal dynamics and related to significant ecosystem services. Grasslands are such crucial surfaces, both in terms of economic and environmental issues and the automatic and frequent monitoring of their agricultural practices is required for many purposes. To address this problem, the deep-based SenDVI framework is presented. SenDVI proposes an object-based methodology to estimate NDVI values from Sentinel-1 SAR observations and contextual knowledge (weather, terrain). Values are regressed every 6 days for compliance with monitoring purposes. Very satisfactory results are obtained with this low-level multimodal fusion strategy (R2 = 0.84 on a Sentinel-2 tile). Finer analysis is however required to fully assess the relevance of each modality (Sentinel-1, Sentinel-2, weather, terrain) and feature sets and to propose the simplest conceivable framework. Results show that not all features are necessary and can be discarded while others have a mandatory contribution to the regression task. Moreover, experiments prove that accuracy can be improved by not saturating the network with non-essential information (among contextual knowledge in particular). This allows to move towards more operational solution.

Performance Analysis of Ionospheric Scintillation Effect on P-Band Sliding Spotlight SAR System

The space-borne P-band synthetic aperture radar (SAR) maintains excellent penetration capability. However, the low carrier frequency restricts its imaging resolution. The sliding spotlight mode provides an operational solution to meet the requirement of high imaging resolution in P-band SAR design. Unfortunately, the space-borne P-band SAR will be inevitably deteriorated by the ionospheric scintillation. Compared with the stripmap mode, the sliding spotlight SAR will suffer more degradation when operating in the scintillation active regions due to its long integration time and complex imaging geometry. In this paper, both the imaging performance and scintillation effect for P-band sliding spotlight mode are studied. The theoretical analysis of scintillation effect is performed based on a refined model of the two-frequency and two-position coherence function (TFTPCF). A novel scintillation simulator based on the reverse back-projection (ReBP) algorithm is proposed to generate the SAR raw data for sliding spotlight mode. The proposed scintillation simulator can also be applied to predict the scintillation effect for other multi-mode SAR systems such as terrain observation by progressive scans (TOPS) and ScanSAR. Finally, a group of simulations are carried out to validate the theoretical analysis.

3D Viewpoint Management and Navigation in Urban Planning: Application to the Exploratory Phase

3D geovisualization is essential in urban planning as it assists the analysis of geospatial data and decision making in the design and development of land use and built environment. However, we noted that 3D geospatial models are commonly visualized arbitrarily as current 3D viewers often lack of design instructions to assist end users. This is especially the case for the occlusion management in most 3D environments where the high density and diversity of 3D data to be displayed require efficient visualization techniques for extracting all the geoinformation. In this paper, we propose a theoretical and operational solution to manage occlusion by automatically computing best viewpoints. Based on user’s parameters, a viewpoint management algorithm initially calculates optimal camera settings for visualizing a set of 3D objects of interest through parallel projections. Precomputed points of view are then integrated into a flythrough creation algorithm for producing an automatic navigation within the 3D geospatial model. The algorithm’s usability is illustrated within the scope of a fictive exploratory phase for the public transport services access in the European quarter of Brussels. Eventually, the proposed algorithms may also assist additional urban planning phases in achieving their purposes.