Reallocation Model Research Articles

Characterization of Top Trading Cycles with single-dipped preferences

In the object reallocation model, when agents’ preferences are unrestricted, Ekici (2024) proves that the top trading cycles is the unique mechanism that is individually-rational, pair-efficient, and strategyproof. We prove that this characterization remains true when agents’ preferences are single-dipped.

The methods of task pre‐allocation and reallocation for multi‐UAV cooperative reconnaissance mission

AbstractNowadays, multi unmanned aerial vehicle (multi‐UAV) systems have been widely used in battlefield. The rationality of mission plan can directly affect the effectiveness of multi‐UAV system. The existing multi‐UAV task allocation model lack a comprehensive modelling of task pre‐allocation and task reallocation issues. However, in actual task execution, task pre‐allocation and task reallocation are a holistic problem. Therefore, based on the background of multi‐UAV cooperative reconnaissance, the authors establish a multi‐UAV cooperative reconnaissance task pre‐allocation and reallocation model (MCRTPR). There are two kinds of task allocation in MCRTPR model. One is task pre‐allocation, which is a static task allocation before the mission begin. Another is task reallocation, that is a dynamic task allocation during the mission. For task pre‐allocation, a particle swarm optimisation algorithm based on experience pool (EPPSO) is proposed. And for task reallocation, the authors design a partial task reallocation algorithm based on contract network protocol (CNP‐PTR). The experimental results show that, compared with some state‐of‐the‐art algorithms, EPPSO can get the lowest fitness value under various experimental conditions, and CNP‐PTR is able to handle task reallocation problem caused by multiple kinds of dynamic events.

Development of a non-radial model for resource reallocation using network data envelopment analysis

Public and private sector organizations continually seek to optimize strategies for sustained competitiveness by reallocating resources efficiently among various institutions. This research introduces a non-radial resource reallocation model employing network data envelopment analysis to address this need. The study introduces an approach to redistributing resources in a dynamic network setting over multiple periods. It takes into account indicators of both negative outcomes, aiming to improve the overall effectiveness and efficiency of companies within a holding structure. The research outlines a methodology, including data collection, modeling assumptions, decision variables, and constraints for implementing this reallocation model. By focusing on resource allocation in network systems over periods, this study provides a solid foundation for enhancing resource allocation efficiency in organizations. Additionally, it addresses the complexities associated with resource allocation compared to settings. The proposed dynamic network DEA model considers both temporal aspects in evaluations. Demonstrates its potential for resource allocation in multi-stage processes through applications within the banking industry. One key finding is the importance of recognizing shared constraints among Decision Making Units (DMUs). Considering the impact of restrictions, like government regulations, on decision-making processes and overall efficiency. The created dynamic network DEA model introduces an inventive method to redistribute resources in intricate organizational setups. It offers perspectives for decision-making procedures. Moreover, it sets the stage for further exploration into different indicators and the impact of diverse government interventions on resource allocation effectiveness.

The association between 24-hour activity, sedentary and sleep compositions and mental health in Australian adults: a cross-sectional study

BackgroundPhysical activity, sedentary behaviour, and sleep are key components to health and well-being. Compositional data analysis of activity data overcomes the limitations of traditional statistical approaches and comprehensively assesses the association of all activities throughout a 24-hour day. Few studies have used compositional analysis to explore associations between movement behaviours and mental health. This study examined the association between 24-hour activity compositions and mental health in middle-aged Australian adults.MethodsThis study used cross-sectional data from participants (n = 322; mean age 40.4 years; 58.1% female; 47.8% university degree; 84.8% partnered) in the longitudinal Annual Rhythms in Adults’ lifestyle and health study (Adelaide, Australia). Activity composition (sleep, sedentary behaviour, light physical activity, and moderate-to-vigorous physical activity) was derived using 24-hour Fitbit accelerometry from the first month of participation (December). Mental health outcomes (depression, anxiety, and stress) were obtained from the Depression Anxiety Stress Scale 21-item short-form (DASS-21). The associations between activity composition (conveyed as isometric log ratios) and DASS-21 scores were examined using compositional multi-level linear regression models with a random intercept for clustering of individuals within families. Using the compositional time reallocation model, expected differences in mental health were examined for hypothetical time reallocations between individual activities.ResultsFavourable associations were observed when time (15 min) was reallocated to light physical activity from sleep (depression: -0.31 [95% CI=-0.57: -0.06]; anxiety: -0.20 [95% CI=-0.37: -0.03] and from sedentary behaviour (depression: -0.29 [95% CI=-0.46: -0.13]; anxiety: -0.14 [95% CI=-0.25: -0.03]; stress: -0.16 [95% CI=-0.31: -0.01]). Detrimental associations were observed when time was reallocated away from light physical activity to sleep (depression: 0.32 [95% CI = 0.07: 0.58]; anxiety: 0.20 [95% CI = 0.03: 0.37]) and to sedentary behaviour (depression: 0.30 [95% CI = 0.13: 0.48); anxiety: 0.15 [95% CI = 0.03: 0.26]; stress: 0.17 [95% CI = 0.01: 0.32]). There were no associations when time was allocated to or from moderate-to-vigorous physical activity.ConclusionThe way adults spend their time across a 24-hour day is associated with their mental health. Spending more time in light physical activity appears favourable if this time is taken from sleep and sedentary behaviour. These findings provide support for “move more, sit less” public health messages.Trial registrationThis study was prospectively registered on the Australian New Zealand Clinical Trial Registry (Trial ID: ACTRN12619001430123) on the 16/10/2019.

Resource reallocation strategies for sustainable efficiency improvement of retail chains

Sustainability is an important agenda for retail businesses in the present times. To create long-term value for customers, retail businesses are required to adopt approaches that can enable them to integrate operational efficiency with concerns for environmental and social sustainability. Optimal deployment of resources among the several stores run by a retail chain, with an objective of maximizing sustainable efficiency, is an enabling step in this direction. This research finds three main contributions to the body of knowledge: (1) resource reallocation models are proposed based on data envelopment analysis (DEA), integrating sustainability in the efficiency measurement model and aiming for improvement in the aggregated efficiency, (2) the proposed models integrate selective centralized and decentralized reallocation decisions according to the input-output characteristics, and (3) different scenarios are explored depending on whether the total resources are to be kept the same or reduced through reallocations according to the management's objectives. The application of the proposed models is illustrated with the case study of a supermarket retail chain.

Constrained-Efficient Capital Reallocation

We characterize efficiency in an equilibrium model of investment and capital reallocation with heterogeneous firms facing collateral constraints. The model features two types of pecuniary externalities: collateral externalities, because the resale price of capital affects collateral constraints, and distributive externalities, because buyers of old capital are more financially constrained than sellers, consistent with empirical evidence. We prove that the stationary equilibrium price of old capital is inefficiently high because the distributive externality exceeds the collateral externality, by a factor of two when we calibrate the model. New investment reduces the future price of old capital, providing a rationale for new-investment subsidies. (JEL D21, D24, D25, D62, E22, G31, G32)

Stock reallocation policy for repairable service parts in case of supply disruptions due to extreme weather events

Climate change and global warming are resulting in extreme weather events that are occurring with increased frequency and intensity. These events often lead to supply disruptions of repairable assemblies which may be more damaging for regular operations of the main equipment (aircrafts and helicopters). In this paper, we design an inventory system for repairable service parts with a central repair facility (Depot) and several service parts inventories at the bases. When a part fails, it is replaced with part from inventory held at the base. The faulty part is transported back to the depot, repaired, and transported back to any of the bases following the stock allocation policy. However, extreme weather events may result in a scenario where the supply lines between the depot and one or more of the bases are disrupted. In such cases, a stock reallocation policy becomes a prudent approach in which the parts are transported within the bases to avoid a backorder situation. In order to service an aircraft or a helicopter at a base with low-level inventory, parts are optimally diverted from another base with higher stock. In this context, we also have to decide about the optimal time for initiating reallocation. We formulated the stock reallocation model as a Markov Decision Process (MDP) that uses an aggregate queuing model to approximate the relative value function (RVF) of the optimal stock reallocation policy. The results of the numerical experiment show that such a rule performs very close to optimality. We also conduct a sensitivity analysis to evaluate the effects of different problem characteristics on the optimality gap.

Multi-energy coordinated and flexible operation optimization and revenue reallocation models for integrated micro energy system considering seasonal and daily load characteristics of different buildings

For pursuing economic and environmental-friendly goals, this paper constructs a regional integrated micro energy system where electricity, heat, cooling, and gas energies are interacted and integrated among buildings. First, independent and collaborative operations of micro energy systems are proposed. Second, seasonal and daily power, heat, and cooling loads of a residential building, a business building, and a mall are depicted. Third, in order to minimize the operation cost, energy consumption and CO2 emission, a multi-energy coordinated flexible operation optimization model of integrated micro energy system is established, and the chaotic particle swarm optimization algorithm is applied to solve the optimization model. A benefit evaluation model is built based on perspectives of energy, economy, and environment to evaluate the optimization results. Then, Shapley method is improved by integrating it with cloud focus theory to more fairly allocate optimized benefits, and influencing indexes for adjusting the weights of participants are proposed. Finally, a case study is conducted. The results indicate that: (1) the integrated micro energy system enabled surplus energy inter-supply among the subsystems, thus realizing interconnection and energy complementarity between micro energy systems; (2) seasonal load characteristics showed the differences among the building subsystems, where the winter load showed more flexibility in energy conversion and inter-supply among the subsystems than the summer load; (3) the improved Shapley method are more effective and fairer for benefit allocation, based on different level of importance of participants; (4) Chaotic particle swarm optimization algorithm are more superior in terms of calculation efficiency and accuracy for optimization solutions.

Dietary restriction and ageing: Recent evolutionary perspectives

Dietary restriction (DR) represents one of the most robust interventions for extending lifespan. It is not known how DR increases lifespan. The prevailing evolutionary hypothesis suggests the DR response redirects metabolic resources towards somatic maintenance at the expense of investment in reproduction. Consequently, DR acts as a proximate mechanism which promotes a pro-longevity phenotype. This idea is known as resource reallocation. However, growing findings suggest this paradigm could be incomplete. It has been argued that during DR it is not always possible to identify a trade-off between reproduction and lifespan. It is also suggested the relationship between reproduction and somatic maintenance can be uncoupled by the removal or inclusion of specific nutrients. These findings have created an imperative to re-explore the nexus between DR and evolutionary theory. In this review I will address this evolutionary conundrum. My overarching objectives are fourfold: (1) to outline some of the evidence for and against resource reallocation; (2) to examine recent findings which have necessitated a theoretical re-evaluation of the link between life history theory and DR; (3) to present alternatives to the resource reallocation model; (4) to present emerging variables which potentially influence how DR effects evolutionary trade-offs.

Implementation of the land reallocation problem using NSGA-II and PESA-II algorithms: a case study in Konya/Turkey

Land consolidation is one of the essential tools to increase productivity in agricultural production. The most important, complex, and time-consuming step is land allocation among the land consolidation stages. For these reasons, it is inevitable to use computer technology to optimize this process. This study used reallocation models based on PESA-II and NSGA-II optimization algorithms to solve the reallocation problem. The methods were compared with the optimization algorithms in the literature and the conventional method obtained by the technician. The applied algorithms have achieved successful results by parcel number, average parcel size, and reallocation cost.

The Human Side of Structural Transformation

We document that nearly half of the global decline in agricultural employment was driven by new cohorts entering the labor market. A new dataset of policy reforms supports an interpretation of these cohort effects as human capital. Using a model of frictional labor reallocation, we conclude that human capital growth led to a sharp decline in the agricultural labor supply, accounting, at fixed prices, for 40 percent of the decrease in agricultural employment. This aggregate effect is halved in general equilibrium and it reflects the role of human capital as both a mediating factor and an independent driver of labor reallocation. (JEL J22, J24, J43, L16, O13, O14, Q10)

Improved Allocation and Reallocation Approaches for Software Trustworthiness Based on Mathematical Programming

Software trustworthiness allocation and reallocation are the symmetry of software trustworthiness measure. They can provide the optimization scheme for trustworthiness development and improvement, according to the requirements. The existing allocation and reallocation models do not consider the absolute majority of software trustworthiness classification; therefore, they cannot be very accurate in the allocation and reallocation of software trustworthiness. In this paper, improved allocation and reallocation models are constructed, which can resolve the above problem, and their polynomial solving algorithms are designed. At the same time, a demonstration application of the improved models and algorithms is given, and the trustworthiness enhancement specification of spacecraft software, based on factory reports, is established, including trustworthiness development specification and trustworthiness improvement specification. This enhancement specification provides a scientific and reasonable theory and method for the delivery acceptance of spacecraft software, from qualitative to quantitative grading acceptance, and furnishes a standard guarantee for the trustworthy development and improvement of such software.

Coordinate transformation method for heat reallocation in the spiral water-cooled wall temperature calculation

Fireside metal temperature is quite important in the safety evaluation of boiler water-cooled wall. While little literature reported the accurate temperature calculation model for spiral water-cooled wall. This paper proposes a coordinate transformation method for heat reallocation in the spiral water-cooled wall temperature calculation. A computational fluid dynamics (CFD) model based on a 600 MW tangentially coal-fired boiler is used to provide the original heat flux distributions under various boiler loads. The reallocated heat distribution directly maps with the flow path of the spiral water-cooled wall. The combination of the heat reallocation model and thermal-hydraulic model is realized in MATLAB platform. The calculated temperature distributions at the outlet of the spiral water-cooled wall agree well with the in-situ data, and the maximum relative errors under 100% BMCR load and 75% THA load are 2.7% and 3.2%, respectively. The numerical results show that the working fluid flow rates of the divided loops are almost equal and the maximum metal temperatures of the spiral water-cooled wall are 732.1 K, 710.4 K, 760.9 K and 792.9 K under 100% BMCR, 75% THA, 50% THA and 35% BMCR loads, respectively. The local overheating is likely to occur in low boiler load. This model is intended to improve the metal temperature calculation method of the spiral water-cooled wall, which could benefit the safety monitoring of the boiler under variable loads.

Read Refresh Scheduling and Data Reallocation against Read Disturb in SSDs

Read disturb is a circuit-level noise in flash-based Solid-State Drives (SSDs), induced by intensive read requests, which may result in unexpected read errors. The approach of read refresh (RR) is commonly adopted to mitigate its negative effects by unconditionally migrating all valid data pages in the RR block to another new block. However, routine RR operations greatly impact the I/O responsiveness of SSDs, because the processing on normal I/O requests must be blocked at the same time. To further reduce the negative effects of read refresh, this article proposes a read refresh scheduling and data reallocation method to deal with two primary issues with respect to an RR operation, including where to place data pages and when to trigger page migrations. Specifically, we first construct a data reallocation model to match the data pages in the RR block and the destination blocks for addressing the issue of where to place the data. The model considers not only the read hotness of pages in the RR block, but also the accumulated read counts of the destination blocks. Moreover, for addressing the issue of when to trigger data migrations, we build a timing decision model to determine the time points for completing page migrations by considering the factors of the intensity of I/Os and the disturb situation on the RR block. Through a series of simulation experiments based on several realistic disk traces, we illustrate that the proposed RR scheduling and data reallocation mechanism can noticeably reduce the read errors by more than 10.3% , on average, and the long-tail latency by between 43.9% and 64.0% at the 99.99th percentile, in contrast to state-of-the-art methods.

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.

Dynamic Reallocation Model of Multiple Unmanned Aerial Vehicle Tasks in Emergent Adjustment Scenarios

Due to their strong risk tolerance, low manufacturing cost and good maneuverability, unmanned aerial vehicles (UAVs) have been widely used in various fields. Among related challenges, coordinated task assignment is a key scientific issue for autonomous control of UAVs. In this paper, based on the idea of fuzzy C-means (FCM) clustering and the ant colony optimization (ACO) algorithm, a cooperative multiple task reallocation problem with target precedence constraints for heterogeneous UAVs is proposed. The contributions of this research are the performance evaluation of the original algorithms in a dynamic context, consideration of changes in some attributes of the environment, and the extension of these algorithms to properly address more realistic dynamic emergent adjustment scenarios. According to the corresponding task reallocation strategy, the scenarios are divided into three categories: the complete redistribution strategy can effectively cope with scenarios where tasks have changed significantly, the partial adjustment strategy can induce partial responses to the changes of individual tasks, and group redistribution can effectively solve the problem of task target threat rating changes. The simulation results show that the dynamic reallocation model of multi-UAV tasks in dynamic emergent adjustment scenarios can achieve better performance to complete the corresponding tasks based on the proposed scheme. In addition, we deployed the developed graphical modeling and analysis software (GMAS) platform to implement the dynamic reallocation model of multi-UAV tasks in dynamic emergent scenarios, and the validity and reliability of the proposed task reallocation model were verified.

Bank credit allocation and productivity: stylised facts for Portugal

PurposeThe linkages between credit allocation and productivity have particular relevance in Portugal. This study aims to investigate whether credit extended by the Portuguese banking system has been allocated to the most productive firms within each sector.Design/methodology/approachWith a data set covering 95% of total outstanding credit to non-financial corporations recorded in the Portuguese credit register, the authors investigate whether outstanding loans by resident banks to 64 economic sectors have been granted to the most productive firms. First, the authors estimate a baseline, reduced-form model of credit reallocation, where the parameter of interest gives the response of total credit granted to each firm to its level of productivity. Second, the authors assess how this response is affected by the share of credit allocated to unproductive firms. Third, the authors redo the analysis with credit granted to each firm by each banking group, instead of by the entire banking system, so that bank indicators can be taken on board.FindingsThe authors find evidence of misallocation, which reflects the joint effects of credit supply and credit demand decisions taken over the course of time, and the adverse cyclical developments following the accumulation of imbalances in the Portuguese economy for a protracted period. In 2008–2016, the share of outstanding credit granted to firms with very low productivity (measured or inferred) was always substantial, peaking at 44% in 2013, and declining afterwards with the rebound in economic activity and the growing allocation of new loans towards lower risk firms and away from higher risk firms. Furthermore, the authors find that misallocation is associated with slower reallocation. The responsiveness of credit growth to firm relative productivity is much lower in sectors with relatively more misallocated credit and when banks have a high share of such credit in their portfolios.Originality/valueBanking system distortions are often mentioned as potential or likely culprits for capital misallocation, but they are not empirically analysed with credit data. The ability to explicitly analyse bank credit and link it to variables pertaining to both firms and banks is a novel feature relative to most previous studies, which largely rely on firm-level or sectoral data alone.

Reallocation model in land consolidation using multi‐objective particle swarm optimization dealing with landowners' rights

AbstractIn conventional reallocation, farmers' preferences are used to determine the location of their new parcels in predetermined blocks. The most common conflict that can arise during this process is that demand may be high for some blocks. The manner of resolving such disputes, which deal directly with landowners' rights, can affect the success or failure of land consolidation projects. In this study, a novel model for land reallocation is proposed which is based on the principle that the initial situation of the landowner's parcels before land consolidation will be comparable with the new situation that includes all of his/her rights. For this, a spatial similarity‐based approach was proposed, taking into account geometric, ownership, physical, and locational criteria. Then, the agricultural land reallocation model (LR‐MOPSO) was developed using the multi‐objective particle swarm algorithm. Three objectives were defined: (1) simultaneous consideration of farmers' priority and spatial similarity criteria; (2) pooling of farmers' fragmented parcels; and (3) optimal placement of parcels within the block. The LR‐MOPSO model was applied to an Iranian case study and results were compared with a conventional approach. With this model decision‐makers in land consolidation projects will be able to redistribute parcels in a more transparent way, while dealing with landowners' rights.

The impact of the variability of parameters related to transport costs and parcel shape on land reallocation results

Land reallocation is a time-consuming but vital stage of land-consolidation projects, hence the many attempts to automate and optimize this process. Transport costs related to distances from parcels to farm buildings and costs related to areas and shapes of parcels reduce the profitability of agricultural production. These factors are taken into consideration in some of land reallocation algorithms as separate, independent parameters.The objective of the study was to demonstrate that it is possible to simplify the optimization of land reallocation with a single, dimensionless parameter, a ratio of costs related to the shape and area of a parcel to transport costs. The linear programming method employed uses binary variables, making it a heuristic research method. The optimization model considers several additional conditions to reflect actual land-consolidation projects better: the result of interviews with landowners; equal holding values before and after reallocation; the reduction of the average distance to parcels.The study has demonstrated how the variability of the proposed parameter affects results of optimization in the form of an objective function of the parcel area, shape, and distance to buildings. The proposed modification improves the versatility of the land reallocation model as it allows the researcher to employ a single parameter, which may vary in time, by region, by initial land fragmentation parameters, or changes in farming inputs prices, including fuel and labour. The results proved that very high variability of the examined parameter translates into no more than 10% increase in the value of the objective function in relation to its minimal, optimal value. The research has demonstrated that it is sufficient to assume a specific ratio of costs related to parcel shape to transport costs to devise a proposal of an optimal boundary arrangement for given economic conditions and area.

A risk-simulation based optimization model for wetland reallocation on Yongding floodplain, China

In this study, a wetland reallocation (WR) plan based on water-indicator is designed to confront various ecological crisis and flood risks on Yonding River Floodplain, China, where converting farmland to wetland (CFW) and water diversion (WD) can be considered to balance the tradeoff between manual land utilization and wetland conservation. A risk-simulation based two-stage stochastic fuzzy (RTF) method is developed for handling multiple uncertainties in a WR issue, which cannot only map various risks (including water shortage, soil loss, flood and pollution) through Geographic Information System (GIS), but also deal with objective / subjective uncertainties in a two-stage context. Through risk-simulation, numbers of risk maps have been obtained based on various WD scenarios, which displayed that ecological risk would be the lowest when water diversion reached 200 x 106m3, while flooding risk would increase. Meanwhile, based on WR optimization, natural-artificial wetland reallocations would decrease ecological loss about US$ 0.92 x 106 at highest. Moreover, the optimized land utilizations under various CFW and WD scenarios have been obtained. This study is useful for policymakers of floodplain to adjust current land utilization strategies with consideration of artificial regulations in a sustainable manner.