Results in Control and Optimization最新文献

{"title":"Analysing the effects of dual time delays and terror funding class in terrorism dynamics","authors":"Annesha Sarmah ,&nbsp;Kaushik Dehingia ,&nbsp;Purnendu Sardar ,&nbsp;Anusmita Das ,&nbsp;Hemanta kr. Sarmah ,&nbsp;Santosh Kumar Choudhary","doi":"10.1016/j.rico.2026.100662","DOIUrl":"10.1016/j.rico.2026.100662","url":null,"abstract":"<div><div>In this paper, we develop a novel five-compartment terrorism dynamics model that explicitly incorporates a terror funding class, thereby capturing the critical role of financial resources in sustaining recruitment, logistics, and operational activities. To better reflect real-world processes, the model introduces two discrete time delays: <span><math><msub><mrow><mi>τ</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span>, representing the indoctrination period required for susceptible individuals to become terrorists, and <span><math><msub><mrow><mi>τ</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span>, denoting the lag associated with transferring terrorists to the recovered or quarantined classes. The main contributions of this work include: (i) the formulation of a funding-integrated terrorism model with dual delays; (ii) a complete mathematical analysis of positivity, boundedness, and equilibrium stability; (iii) derivation of the basic reproduction number <span><math><msub><mrow><mi>ℛ</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span> and a sensitivity analysis identifying the parameters that most strongly influence terrorism persistence; and (iv) a rigorous investigation of delay-induced destabilisation and Hopf bifurcation. For the non-delayed system, we establish conditions ensuring the existence and local stability of the terror-free equilibrium when <span><math><mrow><msub><mrow><mi>ℛ</mi></mrow><mrow><mn>0</mn></mrow></msub><mo>&lt;</mo><mn>1</mn></mrow></math></span> and the terror-persistent equilibrium when <span><math><mrow><msub><mrow><mi>ℛ</mi></mrow><mrow><mn>0</mn></mrow></msub><mo>&gt;</mo><mn>1</mn></mrow></math></span>. For the delayed system, we demonstrate that increasing either <span><math><msub><mrow><mi>τ</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span> or <span><math><msub><mrow><mi>τ</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span> beyond their respective critical thresholds leads to Hopf bifurcations and sustained oscillations, representing recurrent waves of terrorist activity. Numerical simulations are provided to validate the analytical results. Overall, the study offers insight into how the speed of radicalisation, operational delays, and financial resources interact to shape terrorism dynamics, with potential implications for the design of more effective counter-terrorism policies.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"22 ","pages":"Article 100662"},"PeriodicalIF":3.2,"publicationDate":"2026-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146077458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Global mild solutions and total controllability of fuzzy conformable fractional stochastic delay systems with non-instantaneous impulses and Poisson jumps","authors":"Nageshwari Sivakumar,&nbsp;Durga Nagarajan","doi":"10.1016/j.rico.2026.100663","DOIUrl":"10.1016/j.rico.2026.100663","url":null,"abstract":"<div><div>This manuscript is concerned with the solvability and total controllability of the fuzzy stochastic delay differential system with non-instantaneous impulses and Poisson jumps under the conformable fractional derivative, which is new to the literature. Such systems naturally arise in real-world processes where uncertainty, memory effects, and abrupt dynamic changes occur simultaneously. The existence and uniqueness results are obtained for the proposed system using the Banach contraction principle. Next, the global solution is derived with the help of generalised Gronwall’s inequality. Furthermore, the total controllability results are established for the presented fuzzy system. A new class of control functions is introduced to regulate the system at the termination of time intervals and on each impulsive event, while incorporating stochastic disturbances. This approach yields to comprehensive controllability outcomes, often termed as total controllability. In support, an example is given to validate the obtained theoretical outcomes. Furthermore, numerical simulations are presented to illustrate the presented model. The technology under discussion will also be used in a number of practical applications, such as traffic flow regulation, population dynamics, climate-driven environmental processes, communication networks, and medical treatment response systems.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"22 ","pages":"Article 100663"},"PeriodicalIF":3.2,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146077457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sustainable wind farm layout design for maximizing power output and reducing environmental impact","authors":"Khamiss Cheikh ,&nbsp;EL Mostapha Boudi ,&nbsp;Rabi Rabi ,&nbsp;Hamza Mokhliss","doi":"10.1016/j.rico.2026.100664","DOIUrl":"10.1016/j.rico.2026.100664","url":null,"abstract":"<div><div>Wind farm layout design continues to face methodological constraints that limit its applicability under realistic operating conditions. Existing approaches frequently rely on single-objective formulations that prioritize either energy maximization or wake-loss reduction, thereby failing to capture the interdependent trade-offs among power generation, turbulence intensity, and wake-induced performance degradation. In addition, widely adopted wake models often use simplified aerodynamic representations that overlook turbine–turbine coupling effects, while deterministic wind-field assumptions ignore the stochastic variability in wind speed and direction that critically influences wake propagation. These limitations underscore the need for a more comprehensive and physically grounded optimization strategy. This study proposes a tailored multi-objective optimization framework that integrates analytical wake modeling with stochastic environmental characterization to identify efficient turbine placements within the farm boundary. The method concurrently optimizes power output, turbulence attenuation, and wake-related energy deficits while enforcing spatial and operational constraints. Numerical evaluations demonstrate marked performance improvements relative to baseline configurations. Turbines situated in favorable aerodynamic regions (<em>T4</em> and <em>T5</em>) achieve power outputs of <em>1.84–1.89 MW</em>, representing an increase of up to <em>72%</em> compared to downstream turbines subjected to wake interference (<em>1.03–1.13 MW</em>). Turbulence intensity decreases by more than <em>55%</em> (<em>1.20–1.28</em> versus <em>2.58–2.81</em>), and wake-related energy losses are reduced by over <em>60%</em> (0<em>.0065–0.0072</em> versus <em>0.013–0.017</em>). These quantitative gains confirm the efficacy of the proposed optimization framework and highlight its potential for scalability, enhanced aerodynamic fidelity, and integration into future large-scale wind-farm planning and operational decision-support systems.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"22 ","pages":"Article 100664"},"PeriodicalIF":3.2,"publicationDate":"2026-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146077459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of the efficacy of the risk-based X̄ control chart in statistical process control","authors":"Aamir Saghir ,&nbsp;Attila I. Katona ,&nbsp;Csaba Hegedũs ,&nbsp;Zsolt T. Kosztyán","doi":"10.1016/j.rico.2026.100661","DOIUrl":"10.1016/j.rico.2026.100661","url":null,"abstract":"<div><div>Risk-based control charts have recently been introduced to address measurement uncertainty. The statistical properties of a risk-based control chart for detecting a shift have not been studied. In addition to the control chart design, performance evaluation is important for detecting changes in the process. In this paper, the effectiveness of a risk-based <span><math><mover><mrow><mi>X</mi></mrow><mrow><mo>̄</mo></mrow></mover></math></span> control chart (recently introduced) in the presence of measurement uncertainty is investigated. By utilizing a risk-based model that considers the cost of decision outcomes, the impact of measurement uncertainty on the <span><math><mover><mrow><mi>X</mi></mrow><mrow><mo>̄</mo></mrow></mover></math></span> chart’s performance in both in- and out-of-control scenarios is designed and examined. To lessen the risk associated with measurement uncertainty, the Nelder–Mead search technique is employed to find the optimal control limits. The performance metrics include the total decision cost, cost ratio, probability ratio, and average run length. Simulation and real-world data analyses are employed to assess the efficiency of the risk-based chart via various performance metrics. A sensitivity analysis is conducted to identify the constraints and relevance of the risk-based <span><math><mover><mrow><mi>X</mi></mrow><mrow><mo>̄</mo></mrow></mover></math></span> chart in statistical process control.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"22 ","pages":"Article 100661"},"PeriodicalIF":3.2,"publicationDate":"2026-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146023010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling lymphatic filariasis dynamics using Levenberg–Marquardt algorithm-artificial neural networks","authors":"Mussa A. Stephano ,&nbsp;John N. Mlyahilu ,&nbsp;Il Hyo Jung","doi":"10.1016/j.rico.2026.100659","DOIUrl":"10.1016/j.rico.2026.100659","url":null,"abstract":"<div><div>This paper introduces a hybrid Levenberg–Marquard-Artificial Neural Network (LMA-ANN) framework for modeling the complex transmission dynamics of lymphatic filariasis (LF), a debilitating vector-borne neglected tropical disease. The methodology addresses key challenges in data-driven epidemiological forecasting by combining the fast convergence properties of the Levenberg–Marquardt optimization algorithm with the universal function approximation capability of neural networks. We evaluate the proposed framework against four established neural architectures such as Multilayer Perceptron (MLP), Fully Connected Neural Network (FCNN), Convolutional Neural Network (CNN), and Recurrent Neural Network (RNN) using both pristine and Gaussian noise-augmented synthetic datasets generated from a compartmental epidemiological model solved with a high-fidelity Runge–Kutta method. Results demonstrate that the LMA-ANN achieves superior predictive accuracy, with the lowest error metrics of <span><math><mrow><mi>M</mi><mi>A</mi><mi>E</mi><mo>=</mo><mn>0</mn><mo>.</mo><mn>029</mn><mo>,</mo><mi>R</mi><mi>M</mi><mi>S</mi><mi>E</mi><mo>=</mo><mn>0</mn><mo>.</mo><mn>039</mn><mo>,</mo><mi>M</mi><mi>S</mi><mi>E</mi><mo>=</mo><mn>0</mn><mo>.</mo><mn>0015</mn></mrow></math></span> and highest coefficient of determination of <span><math><mrow><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup><mo>=</mo><mn>0</mn><mo>.</mo><mn>990</mn></mrow></math></span> on noise-augmented data, while maintaining computational efficiency with the shortest training of <span><math><mrow><mn>87</mn><mo>.</mo><mn>4</mn><mspace></mspace><mi>s</mi></mrow></math></span> and inference of <span><math><mrow><mn>2</mn><mo>.</mo><mn>9</mn><mspace></mspace><mtext>ms</mtext></mrow></math></span> times. Crucially, the CNN and RNN architectures exhibited worst performance degradation on the noise-augmented dataset, yielding negative <span><math><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span> values of <span><math><mrow><mo>−</mo><mn>0</mn><mo>.</mo><mn>15</mn></mrow></math></span> and <span><math><mrow><mo>−</mo><mn>0</mn><mo>.</mo><mn>42</mn></mrow></math></span> respectively, indicating predictions worse than a simple mean model. This highlights a critical limitation of complex architectures when trained on limited, noisy epidemiological data. The study provides two principal contributions: (1) a robust, computationally efficient LMA-ANN framework that accurately captures LF dynamics under realistic data constraints, and (2) evidence-based guidance for model selection in epidemiological applications, emphasizing that architectural complexity must be carefully matched with data quality and quantity. These findings advance computational methods for infectious disease modeling and offer a generalizable tool for public health decision-making in resource-limited settings.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"22 ","pages":"Article 100659"},"PeriodicalIF":3.2,"publicationDate":"2026-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145977842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal transport and incentive design in multi-agent economic control","authors":"Ramen Ghosh","doi":"10.1016/j.rico.2026.100656","DOIUrl":"10.1016/j.rico.2026.100656","url":null,"abstract":"<div><div>This paper develops a principled framework for incentive design in multi-agent economic systems using tools from optimal transport (OT) theory and decentralized control. We consider a class of stochastic multi-agent environments in which each agent selects actions to minimize individual cost functions that depend on both private preferences and aggregate outcomes. To promote socially desirable allocations, we introduce an OT-based mechanism design approach, where incentives are computed as gradients of a Lagrangian dual formulation over probability measures. Our main results establish: (i) a KKT-type characterization of incentive compatibility in Wasserstein space, (ii) monotonicity and fairness of equilibrium allocations under convex coupling, (iii) structural convexity of cost functionals over coupled agent dynamics, (iv) convergence of iterative market updates to optimal allocations, and (v) efficiency guarantees under decentralized feedback. We demonstrate that fairness and incentive alignment emerge naturally as solutions to constrained OT problems, allowing for scalable, interpretable, and robust economic control policies. This formulation provides a unifying perspective on decentralized optimization, mechanism design, and ergodic fairness in economic networks, and opens new directions for data-driven social planning under uncertainty.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"22 ","pages":"Article 100656"},"PeriodicalIF":3.2,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145977843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing epidemic control: Nash game approach to stochastic modeling with Brownian motion","authors":"Md. Abdullah Bin Masud ,&nbsp;Sharmina Rahman ,&nbsp;Faijun Nesa Shimi ,&nbsp;Mostak Ahmed ,&nbsp;Rathindra Chandra Gope","doi":"10.1016/j.rico.2026.100657","DOIUrl":"10.1016/j.rico.2026.100657","url":null,"abstract":"<div><div>This research expands upon stochastic modeling for COVID-19 management by incorporating Nash game theory to optimize control strategies for disease transmission. Building on our original model, which has integrated Brownian motion and nonlinear dynamics to enhance diagnosis and isolation procedures, we now apply Nash game theory to explore the interactions between multiple control variables. Using Pontryagin’s Maximum Principle for theoretical analysis and MATLAB and Python for numerical simulations, we demonstrate that Nash control offers a more practical approach than traditional game theory for balancing interventions. The model’s performance, validated with Worldometer data, achieves low Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE), underscoring its high predictive accuracy. Our findings suggest that Nash control provides a superior framework for real-time epidemic management by optimizing disease control policies, particularly when coordinating antiviral treatments and isolation measures. This work highlights the advantages of Nash-based strategies in developing robust and adaptive epidemic management systems.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"22 ","pages":"Article 100657"},"PeriodicalIF":3.2,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145977841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stability and weighted l2-gain analysis of discrete-time switched T–S fuzzy systems based on admissible-edge-dependent weighted average dwell time strategy","authors":"Qiang Yu,&nbsp;Lijuan Mao","doi":"10.1016/j.rico.2026.100655","DOIUrl":"10.1016/j.rico.2026.100655","url":null,"abstract":"<div><div>The paper introduces the admissible-edge-dependent weighted average dwell time switching strategy that not only considers the differences and compensation between subsystems, but also takes into account the switching order of subsystems. The global uniform asymptotic stability and weighted <span><math><msub><mrow><mi>l</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span>-gain of a class of discrete-time switched nonlinear systems and its related switched T–S (Takagi–Sugeno) model are studied under the new strategy and the multiple discontinuous Lyapunov function approach. The obtained results present a larger feasible range of switching signals than the existing results. Finally, a numerical example is given to illustrate the validity and superiority of the results.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"22 ","pages":"Article 100655"},"PeriodicalIF":3.2,"publicationDate":"2026-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145926711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Image classification and object detection complexity optimization: Exploring deep learning models on camera trap and surveillance clips","authors":"Hayder Yousif ,&nbsp;Zahraa Al-Milaji","doi":"10.1016/j.rico.2026.100654","DOIUrl":"10.1016/j.rico.2026.100654","url":null,"abstract":"<div><div>Input image size for convolutional neural networks (CNNs) has played a major role in classification accuracy and network speed. Designing a large depth, scale, and resolution CNN model cannot guarantee the best performance because of the problems of overfitting and memorization. On the other hand, object detection models have produced very low performance on event-triggered camera-trap images due to highly dynamic scenes. In this paper, we propose a framework for optimizing image classification in terms of performance and complexity by selecting the convenient deep learning model for each image. Based on the image sequence activation maps, we propose Resolution Selection Model (RSM) that generates a weight value for each image in the sequence. We utilize support vector machine (SVM) and the generated weight from RSM to select the appropriate deep learning model. We utilized EfficientNet models that have different input image resolutions to classify and detect the objects from the scaled images. Our results on camera-trap and surveillance images show the efficacy of the proposed method compared to the state-of-the-art architectures in terms of accuracy and computational complexity.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"22 ","pages":"Article 100654"},"PeriodicalIF":3.2,"publicationDate":"2026-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145926632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stability and optimizing the treatment control of tuberculosis model via numerical approach","authors":"Muhammad Farman ,&nbsp;David Amilo ,&nbsp;Manal Ghannam ,&nbsp;Kottakkaran Sooppy Nisar ,&nbsp;Mohamed Hafez","doi":"10.1016/j.rico.2025.100650","DOIUrl":"10.1016/j.rico.2025.100650","url":null,"abstract":"<div><div>According to World Health Organization data, tuberculosis (TB) affects nearly one-third of the world’s population and causes several million deaths and new cases each year. Recent advances in fractal–fractional differential operators have proven effective in simulating complex real-world problems. In this study, we present a TB model with an emphasis on hospital treatment and public health education, using a fractal–fractional operator under the Mittag-Leffler function. The study focuses on biological feasibility elements such as unique solutions, existence, positivity, and feasible domains. The Lipschitz and growth conditions are used to demonstrate the existence and uniqueness of solutions to the proposed TB system. A next-generation matrix technique is used to calculate the effective reproductive number of tuberculosis to determine its spread. Suitable Lyapunov functionals are developed to demonstrate the global stability of both TB-free and endemic equilibria. Each model parameter’s impact on the effective reproductive number is assessed using a normalized sensitivity index calculation. A numerical iterative method with Newton polynomial interpolation is utilized to demonstrate the usefulness of the proposed model, and numerical simulations show that it is more efficient at various fractional orders. We looked at numerical data from a variety of factors and fractional order values, concentrating on their impact on disease eradication. The simulation results are compared between the Newton polynomial interpolation approach and the fractional Adams–Bashforth–Moulton predictor–corrector method for the model compartments. The fractal–fractional approach essentially combines the complex real-world dynamics of infectious diseases with theoretical mathematics. This approach offers deep insights that help improve public health decision-making and guide successful control measures.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"22 ","pages":"Article 100650"},"PeriodicalIF":3.2,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145926634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}