Allocation System Research Articles

Retraction: Water Supply 21 (4): 1514–1524: Evaluating the stormwater management model to improve urban water allocation system in drought conditions, Jiaping Ren and Majid Khayatnezhad, https://dx.doi.org/10.2166/ws.2021.027

Retraction: <i>Water Supply</i> 21 (4): 1514–1524: Evaluating the stormwater management model to improve urban water allocation system in drought conditions, Jiaping Ren and Majid Khayatnezhad, https://dx.doi.org/10.2166/ws.2021.027

Optimisation goals for efficient construction from reused materials towards a circular built environment

Building materials that are reused in a circular economy context are often non-standard because previous usage has altered their original properties. Material matching algorithms aid design and construction by matching components in stock with those needed in a design. The efficiency of these matches is assessed based on factors such as waste, logistics, and structural applicability. In this paper, we evaluate the efficacy and practicality for design evolution of construction-relevant optimisation goals. We evaluate goals based on their construction-time and design time results, using a software pipeline optimising both the mapping and design. One design was also constructed based on the optimised matching, to assess additional considerations when working component-specific designs. Based on difficulties and inefficiencies observed during fabrication, we propose two alternate matching strategies and compare their effects on the chosen factors. The study reveals that component allocation systems frequently overlook the need for both contingency planning and redundancy in the construction process. Additionally, inaccuracies in inventory tracking can significantly compromise the feasibility of the planned design. The stability of these design assistive techniques strongly affects their ability to be applied in large-volume projects. This implies the need for a new set of objective factors to be incorporated into existing methods of design optimisation.

Waitlist Outcomes for Pediatric Heart Transplantation in the Current Era: An Analysis of the Pediatric Heart Transplant Society Database.

Waitlist mortality (WM) remains elevated in pediatric heart transplantation. Allocation policy is a potential tool to help improve WM. This study aims to identify patients at highest risk for WM to potentially inform future allocation policy changes. The Pediatric Heart Transplant Society database was queried for patients <18 years of age indicated for heart transplantation between January 1, 2010 to December 31, 2021. Waitlist mortality was defined as death while awaiting transplant or removal from the waitlist due to clinical deterioration. Because WM is low after the first year, analysis was limited to the first 12 months on the heart transplant list. Kaplan-Meier analysis and log-rank testing was conducted to compare unadjusted survival between groups. Cox proportional hazard models were created to determine risk factors for WM. Subgroup analysis was performed for status 1A patients based on body surface area (BSA) at time of listing, cardiac diagnosis, and presence of mechanical circulatory support. In total 5974 children met study criteria of which 3928 were status 1A, 1012 were status 1B, 963 were listed status 2, and 65 were listed status 7. Because of the significant burden of WM experienced by 1A patients, further analysis was performed in only patients indicated as 1A. Within that group of patients, those with smaller size and lower eGFR had higher WM, whereas those patients without congenital heart disease or support from a ventricular assist device (VAD) at time of listing had decreased WM. In the smallest size cohort, cardiac diagnoses other than dilated cardiomyopathy were risk factors for WM. Previous cardiac surgery was a risk factor in the 0.3 to 0.7 m2 and >0.7 m2 BSA groups. VAD support was associated with lower WM other than in the single ventricle cohort, where VAD was associated with higher WM. Extracorporeal membrane oxygenation and mechanical ventilation were associated with increased risk of WM in all cohorts. There is significant variability in WM among status-1A patients. Potential refinements to current allocation system should factor in the increased WM risk we identified in patients supported by extracorporeal membrane oxygenation or mechanical ventilation, single ventricle congenital heart disease on VAD support and small children with congenital heart disease, restrictive cardiomyopathy, or hypertrophic cardiomyopathy.

Dynamic RIS partitioning in NOMA systems using deep reinforcement learning

The rapid evolution of wireless communication technologies necessitates innovative solutions to meet the increasing performance requirements of future networks, particularly in terms of spectral efficiency, energy efficiency, and computational efficiency. Reconfigurable Intelligent Surfaces (RIS) and Non-Orthogonal Multiple Access (NOMA) are emerging as promising technologies to enhance wireless communication systems. This paper explores the dynamic partitioning of RIS elements in NOMA systems using Deep Reinforcement Learning (DRL) to optimize resource allocation and overall system performance. We propose a novel DRL-based framework that dynamically adjusts the partitioning of RIS elements to maximize the achievable sum rate and ensure fair resource distribution among users. Our architecture leverages the flexibility of RIS to create an intelligent radio environment, while NOMA enhances spectral efficiency. The DRL model is trained online, adapting to real-time changes in the communication environment. Empirical results demonstrate that our approach closely approximates the performance of the optimal iterative algorithm (exhaustive search) while reducing computational time by up to 90 percent. Furthermore, our method eliminates the need for an offline training phase, providing a significant advantage in dynamic environments by removing the requirement for retraining with every environmental change. These findings highlight the potential of DRL-based dynamic partitioning as a viable solution for optimizing RIS-aided NOMA systems in future wireless networks.

Principles for simulating the organ allocation system.

Principles for simulating the organ allocation system.

Lost in Transplantation: Characterizing Racial Gaps in Physician Organ Offer Acceptance.

There are known racial disparities in the organ transplant allocation system in the United States. However, prior work has yet to establish if transplant center decisions on offer acceptance-the final step in the allocation process-contribute to these disparities. To estimate racial differences in the acceptance of organ offers by transplant center physicians on behalf of their patients. Retrospective cohort analysis using data from the Scientific Registry of Transplant Recipients (SRTR) on patients who received an offer for a heart, liver, or lung transplant between January 1, 2010 and December 31, 2020. Nationwide, waitlist-based. 32,268 heart transplant candidates, 102,823 liver candidates, and 25,780 lung candidates, all aged 18 or older. 1) Association between offer acceptance and two race-based variables: candidate race and donor-candidate race match; 2) association between offer rejection and time to patient mortality. Black race was associated with significantly lower odds of offer acceptance for livers (OR=0.93, CI: 0.88-0.98) and lungs (OR=0.80, CI: 0.73-0.87). Donor-candidate race match was associated with significantly higher odds of offer acceptance for hearts (OR=1.11, CI: 1.06-1.16), livers (OR=1.10, CI: 1.06-1.13), and lungs (OR=1.13, CI: 1.07-1.19). Rejecting an offer was associated with lower survival times for all three organs (heart hazard ratio=1.16, CI: 1.09-1.23; liver HR=1.74, CI: 1.66-1.82; lung HR=1.21, CI: 1.15-1.28). Our study analyzed the observational SRTR dataset, which has known limitations. Offer acceptance decisions are associated with inequity in the organ allocation system. Our findings demonstrate the additional barriers that Black patients face in accessing organ transplants and demonstrate the need for standardized practice, continuous distribution policies, and better organ procurement.

Common definitions and variables are needed for the United States to join the conversation on acute-on-chronic liver failure

Acute-on-chronic liver failure (ACLF) is a variably defined syndrome characterized by acute decompensation of cirrhosis with organ failures. At least 13 different definitions and diagnostic criteria for ACLF have been proposed, and there is increasing recognition that patients with ACLF may face disadvantages in the current United States liver allocation system. There is a need, therefore, for more standardized data collection and consensus to improve study design and outcome assessment in ACLF. In this article, we discuss the current landscape of transplantation for patients with ACLF, strategies to optimize organ utility, and data opportunities based on emerging technologies to facilitate improved data collection.

Waiting for a Liver Transplant in New Mexico; Understanding the State's Multi-layered Adversity.

Contrary to the assumption of consistent medical care for patients with specific illnesses in the United States, research reveals vast inconsistencies and inequalities in healthcare delivery, affecting various aspects such as mental illness diagnosis and management, life expectancy differences, overall mortality rates, and healthcare accessibility due to racial, ethnic, and cultural disparities. Liver transplantation, particularly studied in the context of the state of New Mexico (NM), highlights the multilayered inherent disadvantages faced by its citizens. Despite these challenges, the new liver transplantation allocation system implemented by the Organ Procurement and Transplantation Network (OPTN) in 2020, which focuses on geographic concentric circles rather than donor service areas (DSA), cautiously raises hope for reducing these inequities. The future of decades' worth of adversity remains uncertain, but we are optimistic that New Mexicans' systemic difficulty in getting a new liver would eventually be eased.

Comparative Analysis of Ischemia-Reperfusion Injury in Heart Transplantation: A Single-Center Study Evaluating Conventional Ice-Cold Storage versus the Paragonix SherpaPak Cardiac Transport System.

Since the 2018 allocation system change in heart transplantation (HT), ischemic times have increased, which may be associated with peri-operative and post-operative complications. This study aimed to compare ischemia reperfusion injury (IRI) in hearts preserved using ice-cold storage (ICS) and the Paragonix SherpaPak TM Cardiac Transport System (CTS). From January 2021 to June 2022, consecutive endomyocardial biopsies from 90 HT recipients were analyzed by a cardiac pathologist in a single-blinded manner: 33 ICS and 57 CTS. Endomyocardial biopsies were performed at three-time intervals post-HT, and the severity of IRI manifesting histologically as coagulative myocyte necrosis (CMN) was evaluated, along with graft rejection and graft function. The incidence of IRI at weeks 1, 4, and 8 post-HT were similar between the ICS and CTS groups. There was a 59.3% statistically significant reduction in CMN from week 1 to 4 with CTS, but not with ICS. By week 8, there were significant reductions in CMN in both groups. Only 1 out of 33 (3%) patients in the ICS group had an ischemic time >240mins, compared to 10 out of 52 (19%) patients in the CTS group. During the follow-up period of 8 weeks to 12 months, there were no significant differences in rejection rates, formation of de novo donor-specific antibodies and overall survival between the groups. The CTS preservation system had similar rates of IRI and clinical outcomes compared to ICS despite longer overall ischemic times. There is significantly more recovery of IRI in the early post operative period with CTS. This study supports CTS as a viable option for preservation from remote locations, expanding the donor pool.

From disruption to adaptation: Response of phytoplankton communities in representative impounded lakes to China's South-to-North Water Diversion Project

Impounded lakes are often interconnected in large-scale water diversion projects to form a coordinated system for water allocation and regulation. The alternating runoff and transferred water can significantly impact local ecosystems, which are initially reflected in the sensitive phytoplankton. Nonetheless, limited information is available on the temporal dynamics and assembly patterns of phytoplankton community in impounded lakes responding to continuous and periodic water diversion. Herein, a long-term monitoring from 2013 to 2020 were conducted to systematically investigate the response of phytoplankton community, including its characteristics, stability, and the ecological processes governing community assembly, in representative impounded lakes to the South-to-North Water Diversion Project (SNWDP) in China. In the initial stage of the SNWDP, the phytoplankton diversity indices experienced a decrease during both non-water diversion periods (8.5 %∼21.2 %) and water diversion periods (5.6 %∼12.2 %), implying a disruption in the aquatic ecosystem. But the regular delivery of high-quality water from the Yangtze River gradually increased phytoplankton diversity and mediated ecological assembly processes shifting from stochastic to deterministic. Meanwhile, reduced nutrients restricted the growth of phytoplankton, pushing species to interact more closely to maintain the functionality and stability of the co-occurrence network. The partial least squares path model revealed that ecological process (path coefficient = 0.525, p < 0.01) and interspecies interactions in networks (path coefficient = -0.806, p < 0.01) jointly influenced the keystone and dominant species, ultimately resulting in an improvement in stability (path coefficient = 0.878, p < 0.01). Overall, the phytoplankton communities experienced an evolutionary process from short-term disruption to long-term adaptation, demonstrating resilience and adaptability in response to the challenges posed by the SNWDP. This study revealed the response and adaptation mechanism of phytoplankton communities in impounded lakes to water diversion projects, which is helpful for maintaining the lake ecological health and formulating rational water management strategies.

The Equitable Benefit Approach to guide the assessment of medical and psychosocial factors in liver transplant candidacy.

Lack of available organs poses a significant challenge in meeting the needs of patients with life-threatening liver disease who could benefit from liver transplantation (LT). Psychosocial vulnerability markers have been linked to post-transplant outcomes, raising questions about their use in patient selection. However, their incorporation into selection criteria raises concerns about health equity and potential discrimination. As a result, there is a pressing need to refine fair allocation systems that consider both clinical and psychosocial factors to ensure equitable access and optimize post-transplant outcomes. The Equitable Benefit Approach (EBA) proposed in this paper by the multidisciplinary group of clinical experts in LT from the Italian Society for the Study of the Liver seeks to address these concerns. It presents four procedural principles, the two allocative principles usually applied in transplantation (urgency and utility) and introduces a new one, the principle of health equity. The EBA aims to prioritize patients with the highest transplant benefit while addressing health inequalities. It emphasizes evidence-based decision-making and standardized assessment tools to reliably evaluate psychosocial risk factors. Implementing the EBA involves a multi-step process, including stakeholder engagement, prospective studies to validate its efficacy, development of institutional policies and algorithms, and ongoing monitoring and revision. By following these steps, health care providers can ensure that LT allocation decisions are transparent and responsive to evolving clinical and social contexts. Ultimately, the EBA should offer a comprehensive framework for fair patient selection in LT, considering both biomedical and psychosocial aspects.

Online quality-based privacy-preserving task allocation in mobile crowdsensing

Aimed at the existing problems, such as the improving requirements on privacy, and the low quality of collected data in mobile crowd sensing, one online Quality-based Privacy-preserving Task Allocation (QPTA) mechanism is considered in this paper. First, a travel budget-related polynomial is designed to measure the influence of candidate tasks on the whole task quality, and an online task quality-based allocation model is designed to maximize the total task quality when both the budget and time constraints can be satisfied simultaneously. Second, when the perceived data of task participants and requesters are encrypted values, with the introduction of typical Paillier homomorphic encryption technology, the division, the square root, and the Euclidean distance calculations of the encrypted values are then designed. In this way, the encrypt calculations of the task allocation algorithm are solved, and the data privacy of the task allocation system is thus preserved. Finally, the bilateral privacy analysis of the proposed method is illustrated, and some simulations are carried out to show the effectiveness of the proposed method. Simulation results show that the proposed method can allocate tasks effectively while guaranteeing the privacy of both the participants and requesters. It outperforms the most related methods in terms of average perception quality.

Data Envelopment Analysis-Based Approach to Improving of the Budget Allocation System for Decarbonization Targets

Energy innovation plays an important role in the transition to a zero-carbon economy. Governments in IEA member countries are investing in the R&amp;D, demonstration, and deployment of new energy technologies as part of their energy and climate policies. However, government subsidies for energy innovation are not always efficient in achieving climate policy goals. This paper proposes a two-stage Data Envelopment Analysis model with shared inputs to determine the optimal allocation of public funds for the energy innovation process. The innovation process is divided into two stages: the R&amp;D stage and the commercialization stage. The inputs to the model (budget expenditures for energy innovations) are distributed between the first and second stages. As intermediate products, we use the number of patents in clean energy and hydrocarbon energy. The outputs of the model are the changes in carbon intensity and energy efficiency. This model can be used to assess the effectiveness of government spending on energy innovation. The results show that some IEA member countries should allocate a large part of the fossil fuel technology budget (more than 70%) to the research and development phase. The proposed model can support decision making at the international level to increase the effectiveness of public policies in achieving decarbonization and energy efficiency goals.

Long-term resilience in wastewater management: Optimizing treated wastewater allocation with a dynamic multi-agent approach

Water scarcity poses a significant challenge to sustainable development, necessitating innovative approaches to manage limited resources efficiently. Effective water resource management involves not just the conservation and distribution of freshwater supplies but also the strategic reuse of treated wastewater (TWW). This study proposes a novel approach for the optimal allocation of treated wastewater among three key sectors (user agents): agriculture, industry, and urban green space. Recognizing the intricate interplays among these sectors, System Dynamics (SD) and Agent-Based Modeling (ABM) were integrated in a Complex Adaptive System (CAS) to capture the interactions and feedback mechanisms inherent within treated wastewater allocation systems. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) serves as the optimization tool, enabling the identification of optimal allocation strategies across various management scenarios over a 25-year simulation period. Our research navigates the complexities of long-term resource management, accounting for each sector's evolving its objectives and guidelines along the whole system objectives and strategies. The outcomes demonstrate how treated wastewater can be effectively distributed to support economic and social equity –as the system objectives-while supporting agricultural and industrial growth and enhancing efficiency and social well-being –reflecting individual agent objectives-within the CAS framework. The research explores four distinct management scenarios, each prioritizing different sectors to address water resource management challenges. Notably, all four scenarios align with the strategies required by the ruler (government), providing strategic guidance to water resource managers for decision-making. The simulation results reveal a scenario where all sectors' demands are met, with Scenario 4 emerging as the most effective. Scenario 4 aligned with the objectives and guidelines of each sector, demonstrating significant improvements in the CY (Agriculture agent index; increased from 0.2 to 0.68), IGI (Industry agent index; increased from 1 to 1.63), and GAI (Urban Green Space agent index; increased from 1 to 1.23) indices over the 25-year simulation period. By providing a strategic blueprint for policymakers and stakeholders, this study contributes significantly to the discourse on sustainable water resource management, presenting a replicable model for similar contexts globally, where judicious allocation of treated wastewater is paramount for achieving harmony between human activity and ecological preservation.

Transarterial embolization is an acceptable bridging therapy to hepatocellular carcinoma prior to liver transplantation.

Hepatocellular carcinoma (HCC) is an aggressive malignant neoplasm that requires liver transplantation (LT). Despite patients with HCC being prioritized by most organ allocation systems worldwide, they still have to wait for long periods. Locoregional therapies (LRTs) are employed as bridging therapies in patients with HCC awaiting LT. Although largely used in the past, transarterial embolization (TAE) has been replaced by transarterial chemoembolization (TACE). However, the superiority of TACE over TAE has not been consistently shown in the literature. To compare the outcomes of TACE and TAE in patients with HCC awaiting LT. All consecutive patients with HCC awaiting LT between 2011 and 2020 at a single center were included. All patients underwent LRT with either TACE or TAE. Some patients also underwent percutaneous ethanol injection (PEI), concomitantly or in different treatment sessions. The choice of LRT for each HCC nodule was determined by a multidisciplinary consensus. The primary outcome was waitlist dropout due to tumor progression, and the secondary outcome was the occurrence of adverse events. In the subset of patients who underwent LT, complete pathological response and post-transplant recurrence-free survival were also assessed. Twelve (18.5%) patients in the TACE group (only TACE and TACE + PEI; n = 65) and 3 (7.9%) patients in the TAE group (only TAE and TAE + PEI; n = 38) dropped out of the waitlist due to tumor progression (P log-rank test = 0.29). Adverse events occurred in 8 (12.3%) and 2 (5.3%) patients in the TACE and TAE groups, respectively (P = 0.316). Forty-eight (73.8%) of the 65 patients in the TACE group and 29 (76.3%) of the 38 patients in the TAE group underwent LT (P = 0.818). Among these patients, complete pathological response was detected in 7 (14.6%) and 9 (31%) patients in the TACE and TAE groups, respectively (P = 0.145). Post-LT, HCC recurred in 9 (18.8%) and 4 (13.8%) patients in the TACE and TAE groups, respectively (P = 0.756). Posttransplant recurrence-free survival was similar between the groups (P log-rank test = 0.71). Dropout rates and posttransplant recurrence-free survival of TAE were similar to those of TACE in patients with HCC. Our study reinforces the hypothesis that TACE is not superior to TAE as a bridging therapy to LT in patients with HCC.

The Influence of License Plate Allocation Mechanism on Urban Traffic Management: A Comparative Study of Beijing and Shanghai

Urban traffic management has grown in importance since China’s cities have seen a sharp rise in the number of motor vehicles in recent years. In this context, different cities have launched different license plate allocation mechanisms, among which the license plate auction mechanism in Shanghai and the license plate lottery system in Beijing have a greater impact on urban traffic management. Their roles are undeniable while their drawbacks need to be solved. The license plate allocation system can only alleviate urban road congestion, and it is difficult to fundamentally solve the problem, which also requires the government to continue to study, in order to find a long-term solution to promote the innovative innovation of urban traffic management. This paper focuses on the influence of the Beijing license plate lottery system and Shanghai license plate auction system on urban traffic management, points out the drawbacks of different license plate allocation mechanisms and puts forward suggestions, which can clarify the role of different license plate allocation mechanisms in urban traffic management. In order to improve the license plate allocation mechanism and optimize the development path of the license plate allocation mechanism, it is essential to improve the function mechanism of the license plate allocation mechanism in urban traffic management.

Joint optimal allocation of regional water and land resources considering their mutual feed relationship

Water and land resources are indispensable prerequisites for the sustenance and advancement of human civilization. In recent decades, China has faced significant challenges in managing its water and land resources due to the intensifying competition resulting from rapid urbanization, industrialization, and population growth. The joint optimal allocation of water and land resources can effectively address these issues. However, there have been limited accomplishments in investigating the integrated water and land resources allocation system’s interaction with social, economic, and environmental development. This paper develops a novel joint optimal allocation model of regional water and land resources (JOAMRWLS). The model integrates water and land resources for integrated allocation, taking into account the mutual feed relationship between them, and thereby achieving comprehensive utilization and coordination of water and land resources within the region. Then a two-layer nesting algorithm based on successive approximation and nonlinear programming (SA-NLP) is proposed to solve the model, obtaining the regional optimal land use pattern and optimal water allocation scheme. Subsequently, this paper uses Luoyang City in Henan Province, China, as a case study to verify the proposed JOAMRWLS. The results indicate that the water volume and area of each land use type tend to stabilize after the fifth iteration of the calculation with a consistent water volume of 18.65 × 108 m3. Compared with the conventional optimization model of water resources (COMWR), the JOAMRWLS encompasses five cities experiencing water scarcity, whereas the latter includes twelve such cities. Furthermore, the economic benefit of the JOAMRWLS is 2.65 × 1011 CNY, surpassing that of the former at 2.56 × 1011 CNY, highlighting its superiority.

Communication Patterns Between Companies and Female Drivers Pre- and Post-COVID-19 Pandemic: Evidence from Indonesia

This study aimed to investigate the conditions of Indonesian female drivers in the ride-hailing industry pre- and post-COVID-19 pandemic, focusing on communication patterns between companies in response to changes related to female drivers during these periods. The pandemic has significantly impacted many industries, including ride-hailing, with female drivers being disproportionately affected. Moreover, the pandemic has exacerbated existing workforce challenges for them, such as childcare responsibilities and limited access to transportation. Semistructured interviews with 12 female drivers were conducted in Bandung, Indonesia from March to October 2023. They were asked open-ended questions about their experiences and perspectives regarding their working conditions before and after the pandemic. The results showed that before the pandemic, female drivers faced harsh working conditions, including a higher order cancellation rate than their male counterparts due to social gender stereotypes. After the pandemic, these challenges persisted. They experienced income loss and encountered several abusive customers. Unfortunately, neither the companies nor the government provided adequate support in any of these circumstances. Even though companies have taken steps to protect drivers from coronavirus infection, they have maintained a monopoly and a gender discrimination policy. They have not been transparent about the order allocation system, income deductions, or the criteria for incentive points.

Hybrid intelligent system for channel allocation and packet transmission in CR-IoT networks

The proliferation of interconnected devices is driving a surge in the demand for wireless spectrum. Meeting the need for wireless channel access for every device, while also ensuring consistent quality of service (QoS), poses significant challenges. This is particularly true for resource-limited heterogeneous devices within Internet of Things (IoT) networks. Cognitive radio (CR) technology addresses the shortcomings of traditional fixed channel allocation policies by enabling unlicensed users to opportunistically access unused spectrum belonging to licensed users. This facilitates timely and reliable transmission of mission-critical data packets. A cognitive radio-enabled IoT (CR-IoT) network is poised to better accommodate the growing demands of diverse applications and services within the smart city framework, spanning areas such as healthcare, agriculture, manufacturing, logistics, transportation, environment, public safety, and pharmaceuticals. To minimize switching delays and ensure energy and spectral efficiency, this study proposes a hybrid intelligent system for efficient channel allocation and packet transmission in CR-IoT networks. Leveraging Support Vector Machine (SVM) and Adaptive Neuro-Fuzzy Inference System (ANFIS), the system dynamically manages spectrum resources to minimize handoffs while upholding QoS. A Java-based simulation integrates system outputs with interference temperature data to accommodate service demands across 2G–4G spectrums. Evaluation reveals SVM’s 98.8% accuracy in detecting spectrum holes and ANFIS’s 90.4% accuracy in channel allocation. These results demonstrate significant potential for enhancing spectrum utilization in various IoT applications.

Dynamic Exception Points for Fair Liver Allocation

There are disparities in access to livers based on transplant patients’ height, which disproportionately affects Hispanics, Asians, and women (across all ethnicities), because short patients can receive transplants from a smaller pool of available deceased donors for medical reasons. Reduced likelihood of transplantation leads to higher mortality rates and longer waiting times. We analyze fairness within the current U.S. liver allocation system where patients receive priority dynamically, based on their model for end-stage liver disease (MELD) scores, which reflect the severity of liver disease. We propose a simple adjustment, providing additional (exception) points based on height and MELD score, that can be easily implemented in practice, which materially reduces the disparity without sacrificing overall efficiency. We model the liver allocation system as a multiclass fluid model of overloaded queues with heterogeneous servers. We impose explicit equity constraints for all static patient classes, that is, height. We characterize the optimal solution under the objective of minimizing pretransplant mortality. The discretized version of the optimal policy is numerically solved using estimates from clinical data and a detailed simulation study demonstrates its effectiveness. The optimal policy, called the equity adjusted mortality risk policy, advocates ranking patients based on their short-term mortality risk adjusted for equity among height classes. Interpretation of the shadow prices of equity constraints in the optimal control problem as MELD exception points is novel in the transplant context since they can be seamlessly mapped into the existing system. Our simulations show that for women, the disparity can be almost completely eliminated. Hispanics and Asians greatly benefit from receiving these MELD exception points also. Our work provides a remedy to reduce the disparities in access to liver transplantation within the MELD-based allocation. Our approach can help the on-going analysis of the continuous distribution model for livers because it also considers aspects of candidate biology, notably height and body surface area. Funding: M. Akan was supported by the National Science Foundation [Grant CMMI-1334194] and the Carnegie Mellon University (CMU) [Onetto Fellowship in Operations Management]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/serv.2023.0092 .