Number Of Parcels Research Articles

Hybrid fleet capacitated vehicle routing problem with flexible Monte–Carlo Tree search

The rise in EVs popularity, combined with reducing emissions and cutting costs, encouraged delivery companies to integrate them in their fleets. The fleet heterogeneity brings new challenges to the Capacitated Vehicle Routing Problem (CVRP). Driving range and different vehicles' capacity constraints must be considered. A cluster-first, route-second heuristic approach is proposed to maximise the number of parcels delivered. Clustering is achieved with two algorithms: a capacitated k-median algorithm that groups parcel drop-offs based on customer location and parcel weight; and a hierarchical constrained minimum weight matching clustering algorithm which considers EVs' range. This reduces the solution space in a meaningful way for the routing. The routing heuristic introduces a novel Monte–Carlo Tree Search enriched with a custom objective function, rollout policy and a tree pruning technique. Moreover, EVs are preferred overother vehicles when assigning parcels to vehicles. A Tabu Search step further optimises the solution. This two-step procedure allows problems with thousands of customers and hundreds of vehicles to be solved accomodating customised vehicle constraints. The solution quality is similar to other CVRP implementations when applied to classic VRP test-instances; and its quality is superior in real-world scenarios when constraints for EVs must be used.

Understanding the post-2010 increase in food bank use in England: new quasi-experimental analysis of the role of welfare policy

BackgroundThe number of food banks (charitable outlets of emergency food parcels) and the volume of food distributed by them increased multi-fold in the United Kingdom (UK) since 2010. The overwhelming majority of users of food banks are severely food insecure. Since food insecurity implies a nutritionally inadequate diet, and poor dietary intake has been linked to a number of diseases and chronic conditions, the rise in the number of people using food banks is a phenomenon of significant importance for public health. However, there is a shortage of robust, causal statistical analyses of drivers of food bank use, hindering social and political action on alleviating severe food insecurity.MethodsA panel dataset of 325 local authorities in England was constructed, spanning 9 years (2011/12–2019/20). The dataset included information about the volume of parcels and the number of food banks in the Trussell Trust network, as well as economy-related, welfare system-related and housing-related variables. A quasi-experimental approach was employed in the form of a ‘first differencing’ ecological model, predicting the number of food parcels distributed by food banks in the Trussell Trust network. This neutralised bias from omitting time-constant unobserved confounders.ResultsSeven predictors in the model were statistically significant, including four related to the welfare system: the value of the main out-of-work benefit; the roll-out of Universal Credit; benefit sanctions; and the ‘bedroom tax’ in social housing. Of the remaining three significant predictors, one regarded the ‘supply’ side (the number of food banks in the area) and two regarded the ‘demand’ side (the proportion of working age population on out-of-work benefits; the proportion of working age population who were unemployed).ConclusionThe structure of the welfare system has been partly responsible for driving food bank use in the UK since 2011. Severe food insecurity could be alleviated by reforming aspects of the benefit system that have been evidenced to be implicated in the rise in food bank use. More broadly, the findings provide support for ‘Health and Health Equity in All Policies’ approach to policymaking.

Land consolidation through parcel exchange among landowners using a distributed Spark-based genetic algorithm

Land consolidation is an essential tool for public administrations to reduce the fragmentation of land ownership. In particular, parcel exchange shows promising potential for restructuring parcel holdings, even more when the number of parcels and owners involved is large. Unfortunately, the number of possible exchange combinations grows very quickly with the number of participating landowners and parcels, with the associated challenge of finding an acceptable solution. In this paper, we present a high-performance solution for parcel exchange based on genetic algorithms. Our proposal, using Apache Spark framework, is based on the exploiting of distributed-memory systems with effortless access in order to reduce the execution time. This also allows increasing the search width through multiple populations that share their advances. This can be achieved without compromising the search depth thanks to the higher amount of resources available from using distributed-memory systems. Our proposal is capable of achieving better solutions in lower amounts of time compared to previous works, showing that genetic algorithms on a high performance system can be used to propose fair parcel exchanges under strict time constraints, even in complex scenarios. The performance achieved allows for fast trial of several options, reducing the time usually needed to perform administrative procedures associated with land fragmentation problems. Specifically, our proposal is capable of combining the benefits of both depth-focused and width-focused multithreaded parallelization. It matches the speedup gains of depth-focused multithreaded parallelization. The width-focused parallelization provides local minimum resilience and fitness value reduction potential. In this paper, multithreading solutions and Spark-based solutions are tested.

Cohesive parcellation of the human brain using resting-state fMRI

BackgroundThe data burden for resting-state fMRI analysis rises with increasing resolutions available at ultrahigh fields. Therefore, a fundamental preprocessing step in brain network analysis is to reduce the data, usually by performing some kind of data parcellation. Most functional parcellations based on rsfMRI connectivity are synthesized from the dense connectome. In contrast, most network analyses begin by reducing each parcel to a single exemplar time series. This disconnect between parcel formation and usage assumes that parcel exemplars adequately represent their member voxels, which is not always the case for commonly used parcellations. New methodWe propose to parcellate the brain based on parcel cohesion, a measure of similarity between a parcel’s exemplar and its member voxels. A spatially constrained agglomerative hierarchical framework is used to synthesize parcels based on a minimum cohesion threshold, rather than a predetermined number of parcels. ResultsCohesive parcellation generally results in more parcels than existing approaches. The number of parcels scales with the amount of smoothing in preprocessing, yet retains adequate information to extract common intrinsic functional networks. Comparison with previous methodsCohesive parcellation performs better than several widely used anatomical, functional, and data-driven parcellations on the basis of parcel cohesion and comparably using several traditional measures of cluster validity. ConclusionCohesive parcellation ensures that the way parcels are synthesized directly corresponds to the way they are used in subsequent analyses. The resulting parcels are straightforward to interpret and optimal for downstream analysis.

Proposed outsourcing model for pick-up and delivery processes

In the last few years, we have been active participants in globalization and the rapid growth of online commerce. This trend directly impacts logistics, postal, and courier companies. Challenges are visible in the growth and development of these companies, as well as quality of task execution and the ability to adapt to market conditions. With the impact of the SARS-COV-19 virus on the market, and due to locks during the pandemic, shoppers were forced to buy products online. This effect accelerated the trend of purchases via e-commerce, which increased the number of parcels in the technological phases of pick-up and delivery. These companies are the bearers of the first and last technological phase of shipment transport. Due to the increase in the number of shipments, postal and logistics companies are under great pressure. This is because of certain restrictions introduced during the pandemic, but also because of costs, especially fixed costs in the first and last phase of transport. This paper proposes an outsourcing model for the pick-up and delivery to convert fixed costs into variable ones.

A Study on the Flame-Retardant Performance of Recycled Paper Building Materials Manufactured by 3D Printer

The increase in non-face-to-face lifestyles due to COVID-19 worldwide have shown an increase in delivery services. The number of parcels in 2020 was 3.373 billion, an increase of 20.9% from 2.788 billion in 2019. This phenomenon increased delivery box waste. Against this background, this study attempted to develop building materials from the recycling of delivery boxes. In this study, the self-developed WC (wet cellulose) 3D printer confirmed the standardization and uniform performance of the sample by filling the material supply cylinder with cellulose filaments and spraying the composite material through a 10 mm nozzle. The cellulose filament for a WC 3D printer is based on cellulose extracted from wastepaper, and a cellulose filament composite material is used by mixing additives. After manufacturing a specimen using the WC 3D printer, a reliability test for the flame-retardant performance of the material was conducted according to the ISO 11925-2 test method. As a result of the experiment, flame-retardant performance was confirmed at a 40 wt% or greater ceramic binder content. In addition, the WC 3D printer achieved accurate test results by producing specimens with uniform physical properties. In addition, we confirmed that 3D-printed WC can be used to develop customized building materials that can prevent fire spread.

A public transport-based crowdshipping concept as a sustainable last-mile solution: Assessing user preferences with a stated choice experiment

In this study, we analyse user preferences for a public transport based crowdshipping concept, where users carry parcels along on their ride. The concept offers potential economic, environmental and social benefits over other last-mile solutions. We set up a stated choice experiment in which respondents indicate whether they would be willing to bring a parcel along on their ride, while varying the number of parcels, their size, weight, the compensation and required extra time. Based on data from 524 public transport passengers in the Greater Copenhagen Area, we estimate a mixed logit model and find all main effects to be significant. Our results indicate that young(er) individuals, students and (to a lesser extent) employed and self-employed individuals are more likely to participate in the crowdshipping concept, while old(er) individuals (60 + ) are less willing to participate. Our findings further show that the marginal disutility of time spent retrieving and dropping off parcels is higher for old(er) respondents and individuals with high(er) income, while it is lower for individuals with a short-term education. Finally, we find the value of time to be slightly higher than the official Danish value for waiting time but lower than the value of travel time delay. Findings can inform the design of a crowdshipping system as well as related engagement efforts.

Performance scaling for structural MRI surface parcellations: a machine learning analysis in the ABCD Study.

The use of predefined parcellations on surface-based representations of the brain as a method for data reduction is common across neuroimaging studies. In particular, prediction-based studies typically employ parcellation-driven summaries of brain measures as input to predictive algorithms, but the choice of parcellation and its influence on performance is often ignored. Here we employed preprocessed structural magnetic resonance imaging (sMRI) data from the Adolescent Brain Cognitive Development Study® to examine the relationship between 220 parcellations and out-of-sample predictive performance across 45 phenotypic measures in a large sample of 9- to 10-year-old children (N = 9,432). Choice of machine learning (ML) pipeline and use of alternative multiple parcellation-based strategies were also assessed. Relative parcellation performance was dependent on the spatial resolution of the parcellation, with larger number of parcels (up to ~4,000) outperforming coarser parcellations, according to a power-law scaling of between 1/4 and 1/3. Performance was further influenced by the type of parcellation, ML pipeline, and general strategy, with existing literature-based parcellations, a support vector-based pipeline, and ensembling across multiple parcellations, respectively, as the highest performing. These findings highlight the choice of parcellation as an important influence on downstream predictive performance, showing in some cases that switching to a higher resolution parcellation can yield a relatively large boost to performance.

Comparison of traditional method and genetic algorithm optimization in the land reallocation stage of land consolidation

The land reallocation phase as a process has a direct influence on the success of land consolidation (LC) studies. In Turkey, land reallocation is performed according to ‘farmer preferences’ as determined by interviews with landowners. This traditional method is called the ‘interview-based method’. In land reallocation studies, parcel locations and property rights are re-arranged according to both farmer preferences and project productivity. A variety of solutions is inevitable in this re-arrangement, as the person responsible for the project and the series of criteria involved in the process differ between projects. How acceptable the solution is for landowners, and the expected benefit from an LC project, depends on the determination of an optimal solution. Genetic algorithms (GA) are widely considered to be an effective method for finding the optimum solution.In this study, land reallocation was performed automatically using GA and the results compared with the traditional land reallocation method. The main purpose of this study is to advance a land reallocation model which minimizes human interference while still meeting traditional land reallocation criteria. Both farmer preferences and block occupancy status were taken into consideration in this model by using GA. The polygonal areas (blocks) within which plots were defined were planned according to topography and the road and irrigation systems. The study was tested with real data, and it was observed that the success rate of block placement using GA was 93%, according to the farmer's preferences, and that full occupancy rate in the blocks was 73%. The results derived from both models were compared in terms of number of parcels, average parcel size, number of parcels per landholding, and number of shared parcels; these criteria are commonly accepted as prominent comparison criteria in the relevant literature. The comparison shows that more successful land reallocation results were derived from the GA model than from the interview-based model. A survey of landowners was also conducted to verify the success of the GA method. The results showed that an interactive land reallocation which includes an optimization process through which the landowners are able to change their preferences can be carried out effectively.

A game theoretical analysis of metro-integrated city logistics systems

The spare capacity of metro systems during non-peak hours can be utilized to transport parcels or freight, i.e., metro-integrated logistics systems (MILS). Existing studies regarding MILS mainly focused on operational level issues, e.g., parcel distribution problem and service scheduling problem. Little has been done to understand the strategic interactions between metro and logistics operators in the context of MILS and the resulting system-wide impacts. This study conducts a game theoretical analysis of MILS, where a metro company and a logistics company may work either independently or jointly (non-cooperative or cooperative games). In particular, the logistic company decides the number of parcels assigned to MILS, and the metro company controls the price of the MILS service. We examine the decisions of the metro company and the logistics company under different market power regimes, and quantify the system performance. Numerical studies are conducted to illustrate the analytical observations and provide further understanding. Our results show that introducing MILS has the potential to generate Pareto-improving outcomes for the metro company and the logistics company.

Northern Ireland farm-level management factors for recurrent bovine tuberculosis herd breakdowns.

Bovine tuberculosis (bTB) is a chronic, infectious and zoonotic disease of domestic and wild animals caused mainly by Mycobacterium bovis. This study investigated farm management factors associated with recurrent bTB herd breakdowns (n = 2935) disclosed in the period 23 May 2016 to 21 May 2018 and is a follow-up to our 2020 paper which looked at long duration bTB herd breakdowns. A case control study design was used to construct an explanatory set of farm-level management factors associated with recurrent bTB herd breakdowns. In Northern Ireland, a Department of Agriculture Environment and Rural Affairs (DAERA) Veterinarian investigates bTB herd breakdowns using standardised guidelines to allocate a disease source. In this study, source was strongly linked to carryover of infection, suggesting that the diagnostic tests had failed to clear herd infection during the breakdown period. Other results from this study associated with recurrent bTB herd breakdowns were herd size and type (dairy herds 43% of cases), with both these variables intrinsically linked. Other associated risk factors were time of application of slurry, badger access to silage clamps, badger setts in the locality, cattle grazing silage fields immediately post-harvest, number of parcels of land the farmer associated with bTB, number of land parcels used for grazing and region of the country.

Tinjauan Yuridis Penyelesaian Sengketa Terhadap Alas Hak Atas Tanah (Studi Putusan Nomor: 347/PDT/2014/PT-Mdn)

Land disputes are unavoidable today, this is because various land needs are very high in today's times while the number of land parcels is limited. This demands improvements in the field of land management and use for the welfare of the community and especially legal certainty. The research method used in this paper is a normative juridical method. The research method used is library research and field research. Arrangement of rights regarding the basis of land rights as regulated in Law No. 5 of 1996 concerning Basic Agrarian Principles, regulating several land rights that are on the earth's surface, under the earth's surface, and above the air. The factors causing the frequent emergence of land dispute problems include: the land administration system, especially in terms of land certification, which is not right, the distribution of land ownership is not evenly distributed, the legality of land ownership is based solely on formal evidence (certificates), without regard to productivity. soil. The process of resolving disputes over land rights in decision number: 347 / Pdt / 2014 / PT-Mdn is resolved through the litigation channel, where in the litigation line the judiciary is given the authority to hold authority and adjudicate a dispute. In every dispute resolution process through litigation, the parties involved in the dispute must follow the procedures set out in the procedural law.

Determinants of Crop Diversification in Bangladesh: An Econometric Analysis

This study aims to investigate the factors that influence household behaviour in cultivating the diversified crops on their cultivable land in Bangladesh. Cragg’s alternative tobit model has been applied to a unique rural household level dataset to find the catalysts of crop diversification. The results obtained portrayed a mixed impression of crop diversification in the country. The estimated results have revealed that the male head of household, the accessibility of information, a greater number of farming parcels and the availability of hired labour seem to govern the decision of a farming household to participate in non-rice crop production, while factors such as the total amount of land, agricultural extension service and irrigation facilities influence rice cultivation. Moreover, the findings obtained from the same Cragg’s alternative tobit model estimation for the Aman, Boro and Aus seasons have also revealed a similar depiction of crop diversification in Bangladesh.

Implementation of CHyQMOM in OpenFOAM for the simulation of non-equilibrium gas-particle flows under one-way and two-way coupling

The modeling of dilute gas-particle flows is challenging due to particle-trajectory crossing (PTC). Lagrangian particle tracking can be used, but requires a large number of parcels resulting in high computational costs. A less costly method is the Eulerian number density function (NDF) approach, based on the Boltzmann equation, often solved in terms of lower-order moments of the NDF. In this context the conditional hyperbolic quadrature method of moments (CHyQMOM) was developed and is here implemented for the first time in the OpenFOAM-7, together with high-order advection schemes and a new operator splitting procedure. The resulting solver is used to simulate different test cases: phase segregation problems, collision-less and weakly-collisional PTC flows, asymmetric and symmetric Taylor-Green vortex flow and a dilute gas-particle riser. Results, validated against analytical solutions and predictions obtained with Lagrangian particle tracking, show that the implemented CHyQMOM can be used to handle highly non-equilibrium flows.

A sub+cortical fMRI-based surface parcellation.

Both cortical and subcortical structures are organized into a large number of distinct areas reflecting functional and cytoarchitectonic differences. Mapping these areas is of fundamental importance to neuroscience. A central obstacle to this task is the inaccuracy associated with bringing results from individuals into a common space. The vast individual differences in morphology pose a serious problem for volumetric registration. Surface‐based approaches fare substantially better, but have thus far been used only for cortical parcellation, leaving subcortical parcellation in volumetric space. We extend the surface‐based approach to include also the subcortical deep gray‐matter structures, thus achieving a uniform representation across both cortex and subcortex, suitable for use with surface‐based metrics that span these structures, for example, white/gray contrast. Using data from the Enhanced Nathan Klein Institute—Rockland Sample, limited to individuals between 19 and 69 years of age, we generate a functional parcellation of both the cortical and subcortical surfaces. To assess this extended parcellation, we show that (a) our parcellation provides greater homogeneity of functional connectivity patterns than do arbitrary parcellations matching in the number and size of parcels; (b) our parcels align with known cortical and subcortical architecture; and (c) our extended functional parcellation provides an improved fit to the complexity of life‐span (6–85 years) changes in white/gray contrast data compared to arbitrary parcellations matching in the number and size of parcels, supporting its use with surface‐based measures. We provide our extended functional parcellation for the use of the neuroimaging community.

Five Ways of Characterizing Agricultural Land Use Dynamics and Abandonment from Subsidy Data

Abandonment of agricultural land is a process described from different regions of many industrialized countries. Given the current focus on land use, land use change and food security, it appears highly relevant to develop improved tools to identify and monitor the dynamics of agricultural land abandonment. In particular, the temporal aspect of abandonment needs to be assessed and discussed. In this study, we used the detailed information available through the Norwegian subsidy claim database and analyzed the history of use of unique land parcels through a fourteen-year period. We developed and tested five different statistics identifying these land parcels, their temporal dynamics and the extent of occurrence. What became apparent was that a large number of land parcels existing in the database as agricultural land were taken out of production, but then entered into production again at a later stage. We believe that this approach to describe the temporal dynamics of land abandonment, including how it can be measured and mapped, may contribute to the understanding of the dynamics in land abandonment, and thus also contribute to an improved understanding of the food production system.

Selection of suitable parking lot sites in megacities: A case study for four districts of Istanbul

Parking is one of the biggest challenges faced by megacities experiencing rapid growth. With more than 15 million population and approximately 3 million passenger cars, Istanbul is a megacity having a considerable parking problem. Sustainable planning of the parking lots in the city requires smarter spatial decision making approaches to use limited land resources efficiently. In order to determine the optimum locations for parking supply in the case of four districts of Istanbul, a GIS-based fuzzy analytical hierarchy process (AHP) approach is employed. In this context, the relevant criteria are identified and collected under three main categories: (1) land use, (2) finance and (3) transportation. Raster grid layers are created in GIS for those criteria through spatial data processing and analysis techniques. Those layers are then combined after being weighted with the fuzzy AHP approach. Thus, the scores of all grid cells in the study area are obtained and then transferred to the land parcels to rank them by their suitability. Besides, the parcels are also evaluated with respect to shape and area. Finally, those assigned to the highest ranking category as well as having proper shape and area are recognized as the feasible parcels for parking lot generation and prioritized according to those factors. The findings showed that the GIS-based fuzzy AHP approach applied in this study enabled multi-criteria investigation of each location (i.e. grid cell) in the study area based on highly detailed spatial data and could therefore be used to determine the feasible parcels for parking lot generation. Among the main criteria, transportation had the greatest weight while finance had the least weight. According to the case study, the need for parking and the number of feasible parcels are greater in Uskudar than the other three districts.

Evaluation of the Beypınarı Land Consolidation Project of Erzurum Province in Terms of Quantitative Features

This study was carried out to evaluate the efficiency of the Erzurum-Beypınarı land consolidation project. In the study, primary data were obtained from agricultural enterprises through a survey and secondary data from State Hydraulic Works. The minimum number of questionnaires was determined as 20, taking into account the finite population and a 10% safety margin. Quantitative data of the consolidation project were obtained with the help of the NetCAD program. According to the results obtained from the research, the consolidation rate in the research area was 67.9%. The average parcel size, which was 13.33 decares before consolidation, increased to 28.04 decares after consolidation. The water supply and water usage rates were 55.1% and 17.4%, respectively, between 2000-2012, and these values increased to 100% and 26.8% after consolidation. The ratio of shapeless parcels was 66.8% before Beypınarı consolidation, this value decreased to 15.4% after consolidation. With the consolidation, the length of the in-field road increased 2.67 times, and the rate of parcels directly connected to the road increased from 52% to 100%. Shareholders' sharing of agricultural lands before consolidation efforts resulted in the emergence of new businesses. However, the number of active agricultural enterprises has decreased. When agricultural active enterprises are considered, it has been observed that the number of parcels per enterprise, which was 16.11, decreased to 5.16 after consolidation. The fact that the Beypınarı project area borders the Erzurum Airport and the Kars-Erzincan ring road has transformed the agricultural lands into an attraction center, but made them disposed to misuse. From the research, it was concluded that land consolidation projects are beneficial in terms of quantitative features, but the multiplier effect can be increased by investigating them socially and economically.

Combining Parcel Lockers with Staffed Collection and Delivery Points: An Optimization Case Study Using Real Parcel Delivery Data (London, UK)

Delivering parcels to collection and delivery points (CDPs) is often seen as a better option compared with home delivery. However, if the demand is inhomogeneous, either the parcel locker utilization or the service level (i.e., the number of parcels that can be delivered) is low. Either situation would reduce the financial viability. This paper compares two options to increase the utilization, namely: (i) modular lockers (i.e., numbers of lockers adjusted periodically depending on demand) and (ii) combining parcel lockers with staffed CDPs. The latter has the advantage of a low investment cost of staffed CDPs and a low cost per parcel of parcel lockers. Secondly, the paper calculates the optimal number of lockers at a staffed CDP, assuming that all parcels are placed in the staffed CDP if the parcel locker is full. This method was applied to data collected by a parcel delivery company in London. The advantage of using real world data over one year is that it includes seasonal and daily changes in the parcel demand. The decision support method accounts for parcels not being picked up by customers on the delivery day, returned deliveries, and the net present value (NPV) of the investment. This paper shows that having enough lockers for 100% of all parcels compared with 80% doubles the number of required parcel lockers because of the inhomogeneity of the demand. In addition, combining fixed lockers with staffed CDPs offers greater financial benefits compared with modular lockers in this case study.

Sentinel-1 Time Series for Crop Identification in the Framework of the Future CAP Monitoring

In this upcoming Common Agricultural Policy (CAP) reform, the use of satellite imagery is taking an increasing role for improving the Integrated Administration and Control System (IACS). Considering the operational aspect of the CAP monitoring process, the use of Sentinel-1 SAR (Synthetic Aperture Radar) images is highly relevant, especially in regions with a frequent cloud cover, such as Belgium. Indeed, SAR imagery does not depend on sunlight and is barely affected by the presence of clouds. Moreover, the SAR signal is particularly sensitive to the geometry and the water content of the target. Crop identification is often a pre-requisite to monitor agriculture at parcel level (ploughing, harvest, grassland mowing, intercropping, etc.) The main goal of this study is to assess the performances and constraints of a SAR-based crop classification in an operational large-scale application. The Random Forest object-oriented classification model is built on Sentinel-1 time series from January to August 2020 only. It can identify crops in the Walloon Region (south part of Belgium) with high performance: 93.4% of well-classified area, representing 88.4% of the parcels. Among the 48 crop groups, the six most represented ones get a F1-score higher or equal to 84%. Additionally, this research documents how the classification performance is affected by different parameters: the SAR orbit, the size of the training dataset, the use of different internal buffers on parcel polygons before signal extraction, the set of explanatory variables, and the period of the time series. In an operational context, this allows to choose the right balance between classification accuracy and model complexity. A key result is that using a training dataset containing only 3.2% of the total number of parcels allows to correctly classify 91.7% of the agricultural area. The impact of rain and snow is also discussed. Finally, this research analyses how the classification accuracy depends on some characteristics of the parcels like their shape or size. This allows to assess the relevance of the classification depending on those characteristics, as well as to identify a subset of parcels for which the global accuracy is higher.