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This research develops a data-driven statistical model capable of predicting a US Army Reserve (USAR) unit staffing levels based on unit location demographics. This model provides decision makers an assessment of a proposed station location’s ability to support a unit’s personnel requirements from the local population.

This research first develops an allocation method to overcome challenges caused by overlapping unit boundaries to prevent over-counting the population. Once populations are accurately allocated to each location, we then then develop and compare the performance of statistical models to estimate a location’s likelihood of meeting staffing requirements.

This research finds that local demographic factors prove essential to a location’s ability to meet staffing requirements. We recommend that the USAR and US Army Recruiting Command (USAREC) use the logistic regression model developed here to support USAR unit stationing decisions; this should improve the ability of units to achieve required staffing levels.

This research meets a direct request from the USAREC, in conjunction with the USAR, for assistance in developing models to aid decision makers during the unit stationing process.

The purpose of this paper is to help optimize sustainment logistics for US Army brigade combat teams, which may face challenges in transporting their assigned assets.

This paper develops a simulation framework with an integrated integer programming optimization model. The integer-programming model optimizes sustainment outcomes of supported battalions on a daily basis, whereas the simulation framework analyzes risk associated with shortfalls that may arise over the entire duration of a conflict.

This work presents a scenario reflecting the steady resupply of an infantry brigade combat team during combat operations and presents an in-depth risk analysis for possible fleet compositions.

The risk curves obtained allow decision-makers and commanders to optimize vehicle fleet design in advance of a conflict.

The growth of firms is fundamentally based on selfreinforcing feedback loops, one of the most important of which involves cash flow.When profit margin is positive, sales generate cash, which may then be reinvested to finance the operating cash cycle.We analyze simulations of a sustainable growth model of a generic new venture to assess the importance of taxes, and regulatory costs in determining growth.The results suggest that new ventures are particularly vulnerable to public policy effects, since their working capital resource levels are minimal, and they have few options to raise external funds necessary to fuel their initial operating cash cycles.Clearly, this has potential consequences in terms of gaining competitive advantage from experience effects, word of mouth, scale economies, etc. The results of this work suggest that system dynamics models may provide public policy-makers a cost-effective means to meet the spirit of the U.S. Regulatory Flexibility Act

This study aims to examine ship loading strategies during large-scale military deployments. Ships are usually loaded to a stowage goal of about 65% of the ship's capacity. The authors identify how much cargo to load onto ships for each sailing and propose lower stowage goals that could improve the delivery of forces during the deployment.

The authors construct several mixed integer programs to identify optimal ship loading strategies that minimize delivery timelines for notional, but realistic, problem variables. The authors study the relative importance of these variables using experimental designs, regressions, correlations and chi-square tests of the empirical results.

The research specifies the conditions during which ships should be light loaded, i.e. loaded to less than 65% of total capacity. Empirical results show cargo delivered up to 16% faster with a light-loaded strategy compared to fully loaded ships.

This work assumes deterministic sailing times and ship loading times. Also, all timing aspects of the problem are estimated to the nearest natural number of days.

This research provides important new insights about optimal ship loading strategies, which were not previously quantified. More importantly, logistics planners could use these insights to reduce sealift delivery timelines during military deployments.

Most ship routing and scheduling problems minimize costs as the primary goal. This research identifies the situations in which ships transporting military forces should be light loaded, thereby trading efficiency for effectiveness, to enable faster overall delivery of unit equipment to theater seaports.

Pilot upgrade training is critical to aircraft and passenger safety. This study aims to identify variances in the US Air Force C-130J pilot upgrade training based on geographic location and provide a model to enhance policy that will impact future pilot training efforts that lower cost and increase operator quality and proficiency.

This research employed a mixed-method approach. First, the authors collected data and analyzed 90 C-130J pilots' aviation records and then contextualized this analysis with interviews of experts. Finally, the authors present a modified version of Six Sigma's define–measure–analyze–improve–control (DMAIC) that identifies and reduces the variances in C-130J pilot training, translating into higher quality outcomes.

The results indicate significant statistical variances across geographically separated C-130J pilot training organizations. This leads some organizations to have higher proficiency levels in specific tasks and others with comparative deficiencies. Additionally, the data analysis in this study enabled a recommended number of flight hours in several distinct categories that should be obtained before upgrading a pilot to aircraft commander to enhance standards.

This research was limited to C-130J pilot upgrades, but these results can be implemented within any field that utilizes hours as a measure of experience. Implications from this research can be employed to scope policy that will influence pilot training requirements across all airframes in civilian and military aviation.

This research proposes a process improvement methodology that could be immediately implemented within the C-130J community and, more importantly, in any upgrade training where humans advance into higher echelons of a profession.

This paper aims to raise awareness of a potential planning pitfall and provide recommendations on how to assess and improve upon current practices. In potential conflict areas, such as the Korean Theater of Operations (KTO), military forces are required to store a portion of their ammunition combat load within depots and ammunition supply points under the control of a servicing ammunition company. This necessitates a lengthy retrieval process, as the ammunition company does not have enough resources to serve all customers simultaneously.

The stored combat load (SCL) retrieval process is modeled as a parallel machine scheduling problem and simulated using synthetic requirements. The current system of retrieval is contrasted against a proposed alternate system through a series of simulations scaled across three factors: number of ammunition company Soldiers, number of customer units and number of magazines.

The proposed alternate system demonstrates a significant potential for reducing the makespan of the SCL retrieval process when more than half of the magazines store SCL for multiple customers and there are more than five customers per Soldier.

Transitioning military units from a peacetime standing to full combat readiness as quickly as possible is of immense value within the KTO and other hostile areas with established troops not actively engaged in combat.

This paper recommends new criteria for selecting seaports of embarkation during military deployments. Most importantly, this research compares the current port selection criterion, which is to select the seaport with the shortest inland transport time from the deploying installation, to the proposed port selection criteria, which are to select the seaport based on the shortest combined inland and oceanic transit time to the destination theater.

The authors construct an original integer program to select seaports that minimize the expected delivery timeline for a set of notional, but realistic, deployment requirements. The integer program is solved considering the current as well as the proposed port selection criteria. The solutions are then compared using paired-samples t-tests to assess the statistical significance of the port selection criteria.

This work suggests that the current port selection criterion results in a 10–13% slower delivery of deploying forces as compared to the proposed port selection criteria.

This work assumes deterministic inland transit times, oceanic transit times, and seaport processing rates. Operational fluctuations in transit times and processing rates are not expected to change the findings from this research.

This research provides evidence that the current port selection criterion for selecting seaports for military units deploying from the Continental United States is suboptimal. More importantly, logistics planners could use these recommended port selection criteria to reduce the expected delivery timelines during military deployments.

Several military doctrinal references suggest that planners select seaports based on habitual installation-to-port pairings, especially for early deployers. This work recommends a change to the military's current port selection process based on empirical analyses that show improvements to deployment timelines.

This paper aims to study the function of standardisation in intermodal transport. It identifies where standardisation helps to improve intermodal transport, who is active in intermodal transport standardisation, what types of standards are needed and what the decision-making process and implementation of standards should be like to positively influence the performance of intermodal transportation.

An empirical study is designed to carry out this research project. The empirical study starts with a review of the organisations that are responsible for standardisation and intermodal transport, together with the standards that they have developed, and are developing, so far. It continues with analysing the topics where standardisation helps to improve the performance of intermodal transport. The analysis is based on 12 interviews, followed by desk research, to validate the respondents’ statements.

The results show that intermodal transportation should be distinguished in continental and maritime transport, which require different standards. In maritime transport, the hardware aspects of the system are highly standardised. However, further standardisation of information exchange offers potential to improve the quality of transport. For continental transport, challenges appear in the heterogeneity of infrastructure and loading units used in Europe. For both systems, openness and consensus are main requirements for the development of successful standards.

Standards facilitate interoperability, quality and safety of intermodal transportation, which leads to better performance. This has drawn little attention in the literature. This study addresses this gap and focuses on Europe.

Marine transportation has been faced with an increasing demand for containerized cargo during the past decade. Marine container terminals (MCTs), as the facilities for connecting seaborne and inland transportation, are expected to handle the increasing amount of containers, delivered by vessels. Berth scheduling plays an important role for the total throughput of MCTs as well as the overall effectiveness of the MCT operations. This study aims to propose a novel island-based metaheuristic algorithm to solve the berth scheduling problem and minimize the total cost of serving the arriving vessels at the MCT.

A universal island-based metaheuristic algorithm (UIMA) was proposed in this study, aiming to solve the spatially constrained berth scheduling problem. The UIMA population was divided into four sub-populations (i.e. islands). Unlike the canonical island-based algorithms that execute the same metaheuristic on each island, four different population-based metaheuristics are adopted within the developed algorithm to search the islands, including the following: evolutionary algorithm (EA), particle swarm optimization (PSO), estimation of distribution algorithm (EDA) and differential evolution (DE). The adopted population-based metaheuristic algorithms rely on different operators, which facilitate the search process for superior solutions on the UIMA islands.

The conducted numerical experiments demonstrated that the developed UIMA algorithm returned near-optimal solutions for the small-size problem instances. As for the large-size problem instances, UIMA was found to be superior to the EA, PSO, EDA and DE algorithms, which were executed in isolation, in terms of the obtained objective function values at termination. Furthermore, the developed UIMA algorithm outperformed various single-solution-based metaheuristic algorithms (including variable neighborhood search, tabu search and simulated annealing) in terms of the solution quality. The maximum UIMA computational time did not exceed 306 s.

Some of the previous berth scheduling studies modeled uncertain vessel arrival times and/or handling times, while this study assumed the vessel arrival and handling times to be deterministic.

The developed UIMA algorithm can be used by the MCT operators as an efficient decision support tool and assist with a cost-effective design of berth schedules within an acceptable computational time.

A novel island-based metaheuristic algorithm is designed to solve the spatially constrained berth scheduling problem. The proposed island-based algorithm adopts several types of metaheuristic algorithms to cover different areas of the search space. The considered metaheuristic algorithms rely on different operators. Such feature is expected to facilitate the search process for superior solutions.

This study aims to evaluate the efficiency of various techniques for enhancing indoor air quality (IAQ) in construction. It analyzed the alterations in the concentration of indoor air pollutants over time for each product employed in controlling pollution sources and removing it, which included eco-friendly substances and adsorbents. The study will provide more precise and dependable data on the effectiveness of these control methods, ultimately supporting the creation of more efficient and sustainable approaches for managing indoor air pollution in buildings.

The research investigates the impact of eco-friendly materials and adsorbents on improving indoor air quality (IAQ) in Dubai's tall apartment buildings. Field experiments were conducted in six units of The Gate Tower, comparing the IAQ of three units built with “excellent” grade eco-friendly materials with three built with “good” grade materials. Another experiment evaluated two adsorbent products (H and Z) in the Majestic Tower over six months. Results indicate that “excellent” grade materials significantly reduced toluene emissions. Adsorbent product Z showed promising results in pollutant reduction, but there is concern about the long-term behavior of adsorbed chemicals. The study emphasizes further research on household pollutant management.

The research studied the effects of eco-friendly materials and adsorbents on indoor air quality in Dubai's new apartments. It found that apartments using “excellent” eco-friendly materials had significantly better air quality, particularly reduced toluene concentrations, compared to those using “good” materials. However, high formaldehyde (HCHO) emissions were observed from wood products. While certain construction materials led to increased ethylbenzene and xylene levels, adsorbent product Z showed promise in reducing pollutants. Yet, there is a potential concern about the long-term rerelease of these trapped chemicals. The study emphasizes the need for ongoing research in indoor pollutant management.

The research, while extensive, faced limitations in assessing the long-term behavior of adsorbed chemicals, particularly the potential for rereleasing trapped pollutants over time. Despite the study spanning a considerable period, indoor air pollutant concentrations in target households did not stabilize, making it challenging to determine definitive improvement effects and reduction rates among products. Comparisons were primarily relative between target units, and the rapid rise in pollutants during furniture introduction warrants further examination. Consequently, while the research provides essential insights, it underscores the need for more prolonged and comprehensive evaluations to fully understand the materials' and adsorbents' impacts on indoor air quality.

The research underscores the importance of choosing eco-friendly materials in new apartment constructions for better IAQ. Specifically, using “excellent” graded materials can significantly reduce harmful pollutants like toluene. However, the study also highlights that certain construction activities, such as introducing furniture, can rapidly elevate pollutant levels. Moreover, while adsorbents like product Z showed promise in reducing pollutants, there is potential for adsorbed chemicals to be rereleased over time. For practical implementation, prioritizing higher-grade eco-friendly materials and further investigation into furniture emissions and long-term behavior of adsorbents can lead to healthier indoor environments in newly built apartments.

The research offers a unique empirical assessment of eco-friendly materials' impact on indoor air quality within Dubai's rapidly constructed apartment buildings. Through field experiments, it directly compares different material grades, providing concrete data on pollutant levels in newly built environments. Additionally, it explores the efficacy of specific adsorbents, which is of high value to the construction and public health sectors. The findings shed light on how construction choices can influence indoor air pollution, offering valuable insights to builders, policymakers and residents aiming to promote public health and safety in urban living spaces.