System Constraints Research Articles

Optimización de Procesos mediante Value Stream Mapping en Empresas Dedicadas a la Crianza y Producción de Pollos de Engorde

This case study shows how a company in the poultry sector manages to optimize one of its main processes through the application of lean manufacturing methodologies. The guiding research focused specifically on the chicken management process of one of the company's existing progenies, evaluating critical factors that will influence the effectiveness of the application of a key tool among lean methodologies: the identification and implementation of value stream maps. Broadly speaking, the main premise seeks to direct the reader on how, under a focus on the system constraints, the company adequately adjusted its VSM, dissected its process and equitably and efficiently distributed its poultry houses to significantly reduce the emerging times between its different operations or process steps and optimize the flow in turn in these. This document is of a quantitative, qualitative and comparative analytical nature, from a descriptive methodological perspective of a case study type. It describes the technical problem of the oppressive stagnation in the production lines in fattening farms, relates the theoretical component together with the operation sequence discussed during the field work, establishes the object of the research and makes a comparative study of the continuous process of the target company versus its competitors. Among the contributions to the literature, it synthesizes the characteristic way of life of breeding farms in Colombia, emphasizing mainly the management and application of work scheduling to their productions through operational cycles that may well lead them to live two stages of their development with different scenarios.

Communication Preferences in Pediatric Palliative Care: Insights From Caregivers and Specialists-A Central-Eastern European Perspective.

Effective communication is crucial in pediatric palliative care and is essential to facilitate shared decision making between families and the health care team. This study explored the communication preferences of caregivers and health care specialists in Central-Eastern Europe, a region with unique cultural and health care dynamics. Through qualitative interviews, key communication style preferences and barriers were identified. The results affirm that caregivers need thorough information about their child's illness, symptoms, therapeutic options, and care plans. Pediatric palliative care specialists must deliver this information competently and compassionately. Both caregivers and specialists showed common preferences for clear, timely, and empathetic communication. However, specialists faced challenges in finding time within institutional frameworks to meet these communication needs effectively. These findings highlight the need for pediatric palliative care policies and practices that enable specialists to engage in meaningful, culturally sensitive communication, aligning with caregiver preferences while navigating health care system constraints to enhance caregiver satisfaction and improve patient outcomes.

GENES: An Efficient Recursive zk-SNARK and Its Novel Application in Blockchain

The rapid development of blockchain has significantly promoted research on zero-knowledge proofs (ZKPs), especially zero-knowledge succinct noninteractive arguments of knowledge (zk-SNARK). As is well known, protocol proof and verification time, as well as proof size, are the main obstacles that restrict the implementation of ZKPs in practical applications, so they have become the main concerns of researchers in recent years. This work achieves a new recursive zk-SNARK called GENES, which does not have a trusted setup and is secure under the standard discrete logarithm assumption. GENES is designed from the form of the rank-1 constraint system (R1CS) satisfiability problem. Recursive proof composition is achieved by merging multiple R1CS instances, which transforms the verification of numerous proofs into the verification of a single proof. Moreover, multi-helpers amortize proof commitments in this study, significantly reducing the computational pressure and time cost of proof generation. Compared with previous work, GENES effectively improves the proof time and verification time, but at the cost of larger proof sizes. We provide a blockchain Layer-1 scaling solution leveraging GENES to demonstrate its practicality.

Analysis of Differentiated Teaching Strategies in Middle School English Education

This study examines the implementation of differentiated instruction in Chinese middle school English education, focusing on its theoretical foundations, practical applications, and implementation challenges. Through a comprehensive analysis of international practices and local adaptations, the research explores how differentiated instruction can address the growing diversity of student populations and enhance personalized learning in China's educational context. The study investigates three key dimensions: content differentiation, teaching methods, and assessment approaches, while comparing practices in developed countries like the United States and Australia with China's current educational landscape. The findings reveal significant challenges in implementing differentiated instruction in Chinese middle schools, including resource inequality, teacher capability gaps, and traditional assessment system constraints. However, the research also identifies promising opportunities by integrating modern teaching methods. It contributes to the ongoing discussion of educational reform middle school English education in China. But the findings overlook diverse educational contexts in China, highlighting the need for culturally responsive strategies to adapt international practices to local traditions and student needs.

Integrating BRCA testing into routine prostate cancer care: a multidisciplinary approach by SIUrO and other Italian Scientific Societies

Prostate cancer (PCa) ranks among the most prevalent malignancies in men, with notable associations to Hereditary Breast and Ovarian Cancer Syndrome (HBOC) and Lynch Syndrome, both linked to germline likely pathogenetic variant/pathogenetic variant (LPV/PV) in genes involved in DNA repair. Among these genes, BRCA2 in PCa patients is the most frequently altered. Despite progresses, challenges in BRCA carriers detection persist, with a quarter of PCa cases lacking family history.To address these challenges, a multidisciplinary expert panel from six Italian Scientific Societies, formulated a care pathway to integrate BRCA testing into routine clinical practice in different Italian geographical areas.The development process, promoted by the Italian Society of Uro-Oncology (SIUrO), involved three key stages. A preliminary meeting convened teams from different Italian regions to establish minimal requirements for a mini-counseling program (defined as a pre-test consultation carried out by clinicians responsible of patients’ management) and propose care pathway models. At the same time, a comprehensive survey was launched to highlight regional variations in BRCA testing and identify eventual obstacles to testing activities. A subsequent meeting synthesized care pathway proposals and formulated a unified framework, acknowledging regional legislative variations as enriching factors. Lastly, implementation of the unified framework was promoted by the project faculty and identified regional team leaders.Survey results revealed significant regional disparities in BRCA testing, reimbursement policies, and access to genetic counseling. The proposed mini-counseling program outlined essential steps for patient identification, information provision, and multidisciplinary review, aiming to streamline BRCA testing processes.Expert recommendations emphasized offering tumor genetic testing to metastatic PCa patients eligible for PARP-i treatment and outlined criteria for genetic counseling and germline testing. Key considerations included family history and tumor characteristics.In conclusion, the proposed care pathway represents a critical step towards integrating BRCA testing into routine PCa care, aiming to optimize patient management and familial risk assessment within the constraints of the Italian healthcare system.

Inspiring Muslim Women of the Indian Subcontinent (1857-1947): A Study of Their Lives, Struggles, and Contributions

The Indian subcontinent's fight for independence (1857-1947) witnessed profound social, political, and cultural changes, during which Muslim women encountered a variety of challenges, including patriarchal norms, colonial oppression, and the constraints of the purdah system. These barriers often hindered their educational opportunities, limited their public engagement, and reinforced gender-based roles. Despite such limitations, Muslim women played crucial roles in shaping the political and social climate of the era. This study delves into the lives, struggles, and significant contributions of these women, highlighting how they navigated and resisted societal constraints. It discusses influential figures like Begum Rokeya Sakhawat Hossain, Fatima Jinnah, Abadi Banu Begum, Rashid Jahan, and Ismat Chughtai, whose efforts in education, social reform, literature, and nationalist movements challenged the oppressive frameworks of their time. Through their work, these figures not only propelled the cause of Indian independence forward but also championed the rights of Muslim women and broader social reforms. This research seeks to illuminate their determination, agency, and impact, showcasing how Muslim women were integral to both the fight for national liberation and the pursuit of gender equality. By examining their contributions and the socio-political context in which they acted, this study emphasizes their essential place in the history of India’s independence and the progress of women's rights in the subcontinent.

Factors of progression to severity and death in COVID-19 patients at two health care sites in Bamako, Mali

ObjectivesTo analyze the clinical and biological characteristics and to evaluate the risk factors associated with the mortality of patients with COVID-19 in Commune IV of the District of Bamako.MethodsThe cohort consisted of COVID-19 patients managed from March 2020 to June 2022 at the Bamako Dermatology Hospital and the Pasteur Polyclinic in Commune IV in Bamako. The studied variables were sociodemographic, clinical, and biological. For the analysis of deaths, explanatory variables were grouped into sociodemographic factors, comorbidities and symptoms. Binomial logistic regression models were used to identify mortality associated risk factors.ResultsAmong the 1319 included patients, 38.4% were asymptomatic, 46% and 15.5% developed moderate or severe COVID-19 respectively. The predominant signs were cough (48.5%), respiratory difficulty (24.6%) and headache (19.7%). Male were more common (58.2%). High blood pressure (19.9%) and diabetes (10%) were the main comorbidities. D-dimers < 0.5 μg/l was found in 53.3% of cases and the mean hemoglobin level was 12.9 ± 1.7 g/l. The case fatality rate was 3.71% in our series. In bivariate analysis, age > 60 years, high blood pressure, diabetes, clinical severity, D-dimers < 0.5 μg/l were associated with death. Using binomial logistic regression method, age > 60 years, increased heart rate, disease severity level and mainly acute respiratory distress syndrome (polypnea, difficulty breathing) were the factors found associated with death. After adjusting for all the assessed factors, age < 60 years [aHR = 0.15 (0.06–0.35)] and administration of azithromycin [aHR = 0.31 (0.1–0.97)] were protective factors while higher respiratory rate [aHR = 1.14 (1.07–1.22)] and difficulty breathing [aHR = 3.06 (1.03–9.13)] were risk factors associated with death.ConclusionThese main findings elucidate the factors associated with severity and lethality external of health care system constraints. Advanced age, higher heart rate and the development of respiratory distress were the factors significantly associated with increased fatalities.

Application of quadruple Beltrami state on Saturnian dusty plasma

This investigation explores the potential formation of a relaxed equilibrium state, specifically the quadruple Beltrami state, in a three-component dusty plasma consisting of electrons, ions and negatively charged dust particles. This equilibrium state is derived by employing momentum-balanced equations along with Ampere's law. The quadruple Beltrami state is a composite of four Beltrami states, each associated with four distinct eigenvalues. Using the variational principle, we obtained the same relaxed state based on the system's constraints, which include magnetofluid energy, and the helicity of electrons, ions and dust particles. The unified flow is also derived. Dynamo action is investigated in two configurations: a rectangular geometry and a rectangular geometry with an internal conductor. Small-scale turbulent dynamo behaviour is observed in the former, while large-scale turbulent dynamo effects are noted in the latter. The magnitude of the magnetic field is found to be greater in the configuration with an internal conductor. Additionally, flow profiles are plotted as functions of Beltrami parameters and density variations of plasma species. This study contributes to the understanding of relaxation theory and the underlying physics of systems with an internal conductor, such as Saturn (planetary rings around a magnetosphere) and Jupiter magnetosphere, Uranus, Neptune, etc.

Analysis and assessment of multi-GNSS inter-system bias (ISB) and its benefit on real-time precise point positioning

Abstract To meet the high demand for convergence speed in real-time precise point positioning (RTPPP), this paper comprehensively considers both satellite clock offset services and the PPP user perspective, deriving the inter-system bias (ISB) in detail. Using the precise satellite clock offset products from Wuhan University along with self-computed products, we analyze the datum issues related to satellite clock offsets/ISB, taking into account the effects of daily boundary changes, and propose a reliable ISB product workflow. We examine the statistical characteristics of ISB for different receiver types, highlighting their potential to enhance RTPPP performance as prior constraints. Experimental results indicate that after datum unification, the discontinuity of ISB caused by daily boundary issues can be avoided; the ISB values for the same type of receivers are closely aligned, and the statistical characteristics of ISB remain stable. When utilizing ISB products as prior constraints in the Global Positioning System + BeiDou Navigation Satellite System dual-system RTPPP, the root mean square and convergence time in the East-Up-North direction improve by 18%, 10%, 2%, 8%, 3%, and 1% compared to the original PPP, respectively. For the Global Positioning System + Galileo navigation satellite system, the corresponding improvements are 28%, 26%, 17%, 39%, 31%, and 17%.

No quantum solutions to linear constraint systems in odd dimension from Pauli group and diagonal Cliffords

No quantum solutions to linear constraint systems in odd dimension from Pauli group and diagonal Cliffords

Guaranteed Bounds on Posterior Distributions of Discrete Probabilistic Programs with Loops

We study the problem of bounding the posterior distribution of discrete probabilistic programs with unbounded support, loops, and conditioning. Loops pose the main difficulty in this setting: even if exact Bayesian inference is possible, the state of the art requires user-provided loop invariant templates. By contrast, we aim to find guaranteed bounds , which sandwich the true distribution. They are fully automated, applicable to more programs and provide more provable guarantees than approximate sampling-based inference. Since lower bounds can be obtained by unrolling loops, the main challenge is upper bounds, and we attack it in two ways. The first is called residual mass semantics , which is a flat bound based on the residual probability mass of a loop. The approach is simple, efficient, and has provable guarantees. The main novelty of our work is the second approach, called geometric bound semantics . It operates on a novel family of distributions, called eventually geometric distributions (EGDs), and can bound the distribution of loops with a new form of loop invariants called contraction invariants . The invariant synthesis problem reduces to a system of polynomial inequality constraints, which is a decidable problem with automated solvers. If a solution exists, it yields an exponentially decreasing bound on the whole distribution, and can therefore bound moments and tail asymptotics as well, not just probabilities as in the first approach. Both semantics enjoy desirable theoretical properties. In particular, we prove soundness and convergence, i.e. the bounds converge to the exact posterior as loops are unrolled further. We also investigate sufficient and necessary conditions for the existence of geometric bounds. On the practical side, we describe Diabolo , a fully-automated implementation of both semantics, and evaluate them on a variety of benchmarks from the literature, demonstrating their general applicability and the utility of the resulting bounds.

Adaptive Friction Compensation for Tracking Control With Position Error Constraints of Servo Control Systems: A Switched System Point of View

ABSTRACTThis paper will investigate the adaptive backstepping friction compensator for a class of servo control systems from a switched system point of view. Firstly, by introducing a convergence‐invariant unbounded transformation, the position error bounds are incorporated into the original system. Secondly, an integral term is introduced to increase the robustness and the ‐backstepping technique is utilized to deal with the sign‐indefinite term. Then, an adaptive controller with a Coulomb friction estimator is obtained and the generated closed‐loop error system has the upper block‐triangle structure, which can be treated as a pair of cascade‐connected systems. Further, the common Lyapunov function (CLF) is obtained. The objects of asymptotical tracking with position error constraints and identification of the Coulomb friction coefficient can be realized. By similar methods, we propose adaptive friction compensators for the viscous friction model and the Coulomb &amp; viscous model. Finally, the simulation results demonstrate the advantages of the proposed methods.

Modelling and Neuro-Adaptive Robust Control Algorithms for Solid Fuel Rockets

ABSTRACT This study presents the development of a methodology for designing neuro-adaptive robust controllers based on a reference model associated with an artificial neural network of radial basis functions (ANN-RBF) for solid fuel suborbital rockets. The modelling and neuro-adaptive robust control algorithms for these rockets are presented. Initially, the methodology is evaluated for a robust controller based on a reference model with ANN-RBF for altitude control. The main objective of the control is to suppress the effect of non-linear uncertainties inherent in the process. The method involves mathematical and computational modelling, together with the design of adaptive controllers for stability and performance analysis. The controllers considered include model reference adaptive control (MRAC) techniques and a model reference neuro-adaptive control (MRNAC) approach. The analysis, carried out using computer simulations, evaluates the behavior of each controller in relation to system stability and performance. The final objective is to select the most suitable controller for the suborbital rocket, taking into account the system constraints, robust performance requirements, robust stability, and optimal adaptability. This research promotes the development of adaptive controllers for suborbital rockets, with possible applications in scientific research and commercial launches.

Analyzing market plans for enhanced energy hub efficiency: strategies for integrating multiple energy sources and collaboration

ABSTRACT In this study, we introduce the Archimedes optimization algorithm as a key component of our methodology. The Archimedes algorithm, renowned for its robustness and efficiency, is specifically tailored to handle complex optimization problems encountered in energy management systems. By leveraging its unique capabilities, we ensure precise solutions and rapid convergence even under challenging solution conditions characterized by uncertain energy demand forecasts. The proposed algorithm operates by iteratively refining solutions based on probabilistic load predictions and system constraints. It employs sophisticated optimization techniques to navigate the multi-dimensional solution space efficiently, thereby identifying optimal strategies for energy resource allocation within EHs. By incorporating the Archimedes algorithm into our framework, we can effectively capture the dynamic interactions between various energy carriers and adapt to changing market conditions in real-time. Furthermore, the Archimedes algorithm’s ability to provide near-optimal solutions without the need for exhaustive computational resources makes it particularly well-suited for practical implementation in energy management systems. Its efficiency ensures that decision-makers can obtain actionable insights and make informed decisions quickly, thereby enhancing the operational efficiency and economic viability of EHs. The proposed optimization algorithm outperforms alternatives like Archimedes optimization algorithm (APO) and genetic algorithm (GA). On average, it requires 25% fewer iterations for convergence. Moreover, it achieves a 90% convergence rate within just 50 iterations, compared to 70 iterations for APO and 60 iterations for GA, based on 30 distinct runs.

Research on Design Methods for Immersive Games Based on Virtual Reality

Virtual Reality (VR) technology has rapidly advanced, offering immersive gaming experiences previously unattainable. However, creating truly immersive VR games remains a challenge despite improved hardware. This study investigates effective VR game design with a focus on environment design, interaction mechanics, and narrative and user interface (UI) design. The paper highlights that detailed environments enhance immersion but must balance visual quality with performance to avoid discomfort. It emphasizes the necessity of natural interaction mechanisms while considering system constraints and explores the importance of combining narrative depth with intuitive UI design. The findings suggest that successful VR game design requires a multifaceted approach that integrates detailed environmental elements, natural interactions, and a cohesive narrative. Additionally, the study underscores the significance of audio design and its role in enhancing realism and immersion. These design strategies are essential for achieving high levels of immersion and meeting the growing demand for engaging VR experiences. The research also points out the importance of testing and iterative refinement to ensure that the final product is both functional and enjoyable for users.

MATHEMATICAL MODEL AND OPTIMIZATION ALGORITHM ACCORDING TO THE CRITERIA OF MINIMUM CONTACT STRESS FOR INVOLUTE SPUR GEARS WITH INCREASED CONTACT RATIO

Reducing the mass and dimensions of involute spur gears is an actual task of modern mechanical engineering. One of the perspective ways to solve it is the use of gearing with an increased working tooth depth and profile contact ratio εα ≥ 2. The study is devoted to the development of optimal design methods for such gears. Optimality criteria is formulated as follows: the contact stresses in the pitch point must take a minimum value when all constructive, geometric, kinematic, and technological constraints are met, first, when the profile contact ratio εα ≥ 2 is ensured. Variables planning are defined. These are addendum coefficients of the basic racks tooth for pinion and wheel h*a1, h*a2; profile angle of the basic rack α; addendum modification coefficient of the pinion x1. Formed a system of constraints for the variables planning: the main functional constraint of the minimum value of the profile contact ratio: εα ≥ 2; constraint for the addendum coefficients of the basic racks tooth for pinion and wheel h*a1, h*a2; constraint for profile angle of the basic rack α; constraint for addendum modification coefficients x1, x2; absence of the cutter interference for tooth dedendum; absence of the sharpening for tooth addendum; absence of the mesh interference; ensuring the bending strength of pinion and wheel teeth. A method for solving the problem of optimal design is chosen. The method of probing the space of design parameters was chosen from all the variety. The points of the LPτ-sequence are used as test points. The method allows you to operate with a significant number of parameters – up to 51, provides a sufficiently large number of evenly distributed test points – up to 220. The algorithm for optimal design of gear has been developed. The main stages of the algorithm are as follows: setting input data (numerical constraints on design variables, gear parameters and its load); generation of LPτ-sequence for variables planning with simultaneous consideration of their numerical constraints; checking of functional constraints; additional verification calculations (if necessary) of the gearing contact strength; formation of an array of possible solutions; searching of the best solution variant (the test point corresponding to the minimum value of the objective function) by sorting the array.

Design study of a camera system for Earth observation as a payload on the small satellite ROMEO

AbstractThe importance of a safe food supply has increased due to climate change and its consequences. The number and severity of floods, droughts and plant diseases are rising which causes massive crop failures. Early and precise detection of plant diseases can lower crop failures as it enables early containment. Moreover, it promotes the targeted use of pesticides to protect the biodiversity. Satellite sensors improve the detection of plant diseases by enabling frequent and extensive vegetation observation. Hence, we present the design of a camera system for Earth observation on small satellites with a focus on the detection of plant diseases. The disease detection of sugar beets was chosen as the primary objective due to their importance for the German agriculture. This work is divided into two parts. First, the spectra of sugar beets are analyzed to determine spectral channels for a camera system. Second, a camera system is defined to capture spectral information within the previously defined wavelength ranges. The spectra of healthy and diseased sugar beets were measured in fields for agricultural research in Central Germany using a portable spectroradiometer. The investigated diseases are Cercospora leaf spot and virus yellows, which are among the most important pathogens worldwide. Based on the measured data, the so-called Normalized Difference Sugar Beet Index (NDSBI) is defined, which is a custom index to detect these diseases. We can prove that this index enables more precise detection of these sugar beet diseases than existing indices like the Normalized Difference Vegetation Index (NDVI). The camera system is designed as a payload for the small satellite Research and Observation in Medium Earth Orbit (ROMEO), which is being developed at the University of Stuttgart’s (US) Institute of Space Systems (IRS). The proposed design fulfills the high radiation requirements as well as the system constraints of mass and volume. Three different options for the camera system are developed: two designs for the development at the US, one with lens optics and one with mirror optics, and an adjusted commercial camera system. All defined camera systems permit the measurement of the NDSBI to precisely detect sugar beet diseases.

New Advanced Strategy for Controlling the Charging and Discharging of a Storage Unit in a Microgrid Using a Finite Control Set Predictive Model

Storage units are critical in microgrids to ensure stable operation, making optimal and robust control during charging and discharging essential. In this work, we propose a novel finite control set model predictive control (FCS-MPC) strategy to manage the charging and discharging of a battery in a DC microgrid powered by renewable energy. Unlike traditional Proportional-Integral (PI) controllers, the FCS-MPC approach optimizes control actions in real-time, considering system constraints and providing enhanced dynamic response. This work demonstrates the superiority of FCS-MPC in controlling a bi-directional DC/DC converter under various test scenarios, ensuring continuous power supply to a 15W DC load. Simulations in Matlab/Simulink validate the proposal, showing that the FCS-MPC delivers higher efficiency and better performance compared to the PI controller.

Validity of Wearable Inertial Sensors for Gait Analysis: A Systematic Review.

Background/Objectives: Gait analysis, traditionally performed with lab-based optical motion capture systems, offers high accuracy but is costly and impractical for real-world use. Wearable technologies, especially inertial measurement units (IMUs), enable portable and accessible assessments outside the lab, though challenges with sensor placement, signal selection, and algorithm design can affect accuracy. This systematic review aims to bridge the benchmarking gap between IMU-based and traditional systems, validating the use of wearable inertial systems for gait analysis. Methods: This review examined English studies between 2012 and 2023, retrieved from the Scopus database, comparing wearable sensors to optical motion capture systems, focusing on IMU body placement, gait parameters, and validation metrics. Exclusion criteria for the search included conference papers, reviews, unavailable papers, studies without wearable inertial sensors for gait analysis, and those not involving agreement studies or optical motion capture systems. Results: From an initial pool of 479 articles, 32 were selected for full-text screening. Among them, the lower body resulted in the most common site for single IMU placement (in 22 studies), while the most frequently used multi-sensor configuration involved IMU positioning on the lower back, shanks, feet, and thighs (10 studies). Regarding gait parameters, 11 studies out of the 32 included studies focused on spatial-temporal parameters, 12 on joint kinematics, 2 on gait events, and the remainder on a combination of parameters. In terms of validation metrics, 24 studies employed correlation coefficients as the primary measure, while 7 studies used a combination of error metrics, correlation coefficients, and Bland-Altman analysis. Validation metrics revealed that IMUs exhibited good to moderate agreement with optical motion capture systems for kinematic measures. In contrast, spatiotemporal parameters demonstrated greater variability, with agreement ranging from moderate to poor. Conclusions: This review highlighted the transformative potential of wearable IMUs in advancing gait analysis beyond the constraints of traditional laboratory-based systems.

Unravelling the Constraints Associated with Groundnut Marketing: A Comprehensive Review

This review identifies and analyzes constraints in groundnut marketing systems, particularly for smallholder farmers in developing regions. It proposes strategies to enhance efficiency, profitability, and sustainability, thereby improving farmers' livelihoods. A comprehensive literature review of academic journals, policy reports, and case studies identifies key constraints in groundnut marketing. The review utilizes a structured conceptual framework that encompasses supply chain structure, market dynamics, institutional and policy environments, socioeconomic factors and draws on theoretical foundations such as Transaction Cost Economics, Value Chain Analysis, Market Structure-Conduct-Performance Paradigm, Rural Livelihoods Framework, and Supply Chain Risk Management. The study also applied economic and supply chain management theories to groundnut marketing, emphasizing the relevance of Transaction Cost Economics, Value Chain Analysis, and the Market Structure-Conduct-Performance Paradigm. This theoretical framework can be adapted for other agricultural commodities facing similar constraints. The review identifies critical constraints in groundnut marketing, including fluctuating market prices, inadequate storage facilities, limited access to credit, lack of market information, and high transaction costs. These are exacerbated by poor infrastructure, fragmented supply chains, and socioeconomic barriers, indicating the need for holistic, context-specific interventions. The review suggests practical interventions including investment in infrastructure development, enhancing market information accessibility through digital platforms, fostering farmer cooperatives, and implementing price stabilization mechanisms. These measures can empower smallholder farmers, improve market access, and increase profitability. Policymakers, development agencies, and private sector stakeholders can leverage these insights to formulate targeted support programs for groundnut farmers.