Results in Control and Optimization最新文献

{"title":"Intentionally-underestimated value function at terminal state for temporal-difference learning with mis-designed reward","authors":"Taisuke Kobayashi","doi":"10.1016/j.rico.2025.100530","DOIUrl":"10.1016/j.rico.2025.100530","url":null,"abstract":"<div><div>Robot control using reinforcement learning has become popular, but its learning process often terminates midway through an episode for safety and time-saving reasons. This study addresses the problem of the most popular exception handling that temporal-difference (TD) learning performs at such termination. That is, by forcibly assuming zero value after termination, unintentional implicit underestimation or overestimation occurs, depending on the reward design in the normal states. If the termination by failure is highly valued with the unintentional overestimation, the wrong policy may be acquired. Although this problem can be avoided by paying attention to the reward design, it is essential in the practical use of TD learning to review the exception handling at termination. Therefore, this paper proposes a method to intentionally underestimate the value after termination to avoid learning failures due to the unintentional overestimation. This intentional underestimation is heuristically derived with the assumption of two-step transition to absorbing state. In addition, the degree of underestimation is adjusted according to the degree of steadiness at termination, thereby preventing excessive exploration due to the intentional underestimation. Simulation results showed that the proposed method improves the success rate for 24 tasks with different reward designs from 10/24 in the conventional method to 20/24. Real-robot experiments also demonstrated that the proposed method enables to learn the optimal policy even in the case that the conventional method fails.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"18 ","pages":"Article 100530"},"PeriodicalIF":0.0,"publicationDate":"2025-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143175199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diegif: An efficient and secured DICOM to EGIF conversion framework for confidentiality in machine learning training","authors":"Abdullah Al Siam ,&nbsp;Md Maruf Hassan ,&nbsp;Md Atikur Rahaman ,&nbsp;Masuk Abdullah","doi":"10.1016/j.rico.2025.100515","DOIUrl":"10.1016/j.rico.2025.100515","url":null,"abstract":"<div><div>Medical imaging plays a critical role in contemporary healthcare, although it confronts issues relating to storage, security, and confidentiality in machine learning-based diagnostic systems. The proposed framework, <em>Diegif</em>, presents an efficient and safe mechanism for converting DICOM (Digital Imaging and Communications in Medicine) data into EGIF (Encrypted Graphics Interchange Format) files to overcome these challenges. The framework comprises four key components: (1) converting DICOM files to GIF format with encryption, (2) decrypting EGIF files for processing, (3) enabling confidentiality-preserving machine learning training using EGIF data, and (4) facilitating physician diagnosis and report generation based on trained machine learning models. The <em>Diegif</em> framework aims to enhance storage efficiency by decreasing file sizes by 66.32%, thereby improving data transport efficacy and cloud storage affordability while preserving strong encryption for data confidentiality. Pseudocode algorithms are provided for each phase, ensuring reproducibility and transparency. This paper illustrates the framework’s potential to medical image processing, secure storage, and AI-driven diagnostic functions in healthcare.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"18 ","pages":"Article 100515"},"PeriodicalIF":0.0,"publicationDate":"2025-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143175201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mixed-type duality approach for interval-valued programming problems with vanishing constraints","authors":"Vivek Singh,&nbsp;Neelima Shekhawat","doi":"10.1016/j.rico.2025.100527","DOIUrl":"10.1016/j.rico.2025.100527","url":null,"abstract":"<div><div>In this article, we present a new mixed-type dual problem for the challenging class of the interval-valued optimization problem with vanishing constraints. The introduced dual problem does not directly include the index set, but it still requires calculations related to index sets, which makes it challenging to address these models from an algorithm perspective. The relationship between the original interval-valued programming problem with vanishing constraints and its mixed-type dual are discussed by weak, strong and strict converse duality theorems using the assumption of generalized convexity. We also present a non-trivial example to illustrate the theoretical aspects. Our proposed interval-valued mixed-type dual technique unifies the dual techniques discussed in Hu et al. (2020).</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"18 ","pages":"Article 100527"},"PeriodicalIF":0.0,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143175200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Theoretical and numerical study of profit in agricultural sector model using wavelet method","authors":"Yeshwanth R.,&nbsp;Kumbinarasaiah S.","doi":"10.1016/j.rico.2025.100526","DOIUrl":"10.1016/j.rico.2025.100526","url":null,"abstract":"<div><div>Agriculture is crucial in India’s economy and society, supporting rural livelihood and national food security. India is one of the world’s largest agricultural producers, with diverse crops and farming practices. This work aims to present the Chebyshev wavelet collocation method (CWCM) for assessing and producing a numerical approximation of profit in a fractional-order agriculture sector model. Together, numerical simulations and mathematical modeling analysis enhance agricultural management and understanding while offering crucial insights into the dynamics of agricultural profit. Numerical results are obtained from a mathematical and financial perspective using the model parameters for model validation. Additionally, the error and convergence analysis of the Chebyshev wavelets has been presented to assess the applicability of the proposed approach. This study aims to construct Chebyshev wavelet operational matrix of integration (OMIs) and apply them to the numerical solution of fractional differential equations representing the agriculture model. The operational matrices are used to simplify fractional differential equations to an algebraic system of equations. Finally, we graphically depict the results and offer empirical support for our theoretical conclusions through graphic representations. The CWCM approach generates precise results with better absolute error (Ae) for highly nonlinear scenarios by computing a small number of terms and avoiding data rounding. The results of the developed method, the RK4 method, and the ND solver have been compared. The numerical findings demonstrate how well (CWCM) solves the fractional order agriculture model in terms of accuracy and efficiency. Mathematica is a mathematical program used for numerical calculations and implementation.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"18 ","pages":"Article 100526"},"PeriodicalIF":0.0,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143175198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance analysis of a queueing system with tandem nodes, retrial and server vacations","authors":"K. Anitha,&nbsp;V. Poongothai,&nbsp;P. Godhandaraman","doi":"10.1016/j.rico.2025.100520","DOIUrl":"10.1016/j.rico.2025.100520","url":null,"abstract":"<div><div>In this proposed work, we consider a Markovian model of two-stage tandem queueing system with retrial policy and server vacation. The arriving customers are directed to the first station for service if server is idle upon arrival. Otherwise, they will enter into the orbit for retrial. These customers will generate a continuous stream of request for service in a random period of time. After completing the first station service, the customers will enter into the second station. Once the customers receive their service in both stations, they will depart from the system forever. It is mandatory for all the arriving customers to come across both the service stations. When no more customers are present in the orbit, the servers will leave for vacation. The balance equations of birth–death transitions are solved using the recursive approach. Various system performance measures are obtained and the effect of parameters were illustrated graphically.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"18 ","pages":"Article 100520"},"PeriodicalIF":0.0,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143453839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of awareness in self–monitoring of COVID-19: An optimal control approach","authors":"Piu Samui ,&nbsp;Jayanta Mondal ,&nbsp;Amar Nath Chatterjee ,&nbsp;Fahad Al Basir","doi":"10.1016/j.rico.2024.100513","DOIUrl":"10.1016/j.rico.2024.100513","url":null,"abstract":"<div><div>COVID-19 has been a significant global health concern since the last quarter of 2019, prompting ongoing research to understand the transmission patterns and develop global intervention methods. This article presents a Scompartmental model that demonstrates the effectiveness of self-monitoring among individuals as a non-pharmaceutical method in reducing infection progression. The existence of equilibria and their stability have been studied on the basic of the basic reproduction number (<span><math><msub><mrow><mi>R</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span>). We observed forward bifurcation at <span><math><mrow><msub><mrow><mi>R</mi></mrow><mrow><mn>0</mn></mrow></msub><mo>=</mo><mn>1</mn></mrow></math></span>. We have applied optimal control theory and formulated a three control parameters optimal control problem (OCP) to study non-therapeutic measures like increasing awareness of COVID-19 among susceptible and symptomatic individuals and therapeutic measures like providing improved treatment to hospitalized individuals. The cost-effectiveness of these strategies is also analyzed, suggesting the coexistence of possible treatment routes in controlling the virus.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"18 ","pages":"Article 100513"},"PeriodicalIF":0.0,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143175196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Daily allocation of energy consumption forecasting of a power distribution company using optimized least squares support vector machine","authors":"Marzia Ahmed ,&nbsp;Mohd Herwan Sulaiman ,&nbsp;Md. Maruf Hassan ,&nbsp;Md. Atikur Rahaman ,&nbsp;Mohammad Bin Amin","doi":"10.1016/j.rico.2025.100518","DOIUrl":"10.1016/j.rico.2025.100518","url":null,"abstract":"<div><div>Accurate energy consumption forecasting is critical for efficient power distribution management. This study presents a novel approach for optimal allocation forecasting of energy consumption in a power distribution company, utilizing the Least Squares Support Vector Machine (LSSVM) optimized by novel variants of the Barnacle Mating Optimizer (BMO) such as the new Gooseneck Barnacle Optimizer and Selective Opposition-based constrained BMO. The optimized LSSVM hyper-parameters, specifically the regularization parameter (<span><math><mi>γ</mi></math></span>) and the kernel parameter (<span><math><msup><mrow><mi>σ</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span>), were applied to test data to enhance accuracy guided by the Mean Absolute Prediction Error (MAPE), ensuring precise alignment of forecasted values with actual energy consumption data. The results indicate that the novel gooseneck barnacle base-optimized LSSVM provides a robust and reliable solution with accuracy 99.98% for daily energy consumption for allocation forecasting, making it a valuable tool for power distribution companies aiming to optimize their resource allocation and planning processes.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"18 ","pages":"Article 100518"},"PeriodicalIF":0.0,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143175197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal control applied to a stage-structured cassava mosaic disease model with vector feeding behavior","authors":"Eva Lusekelo ,&nbsp;Mlyashimbi Helikumi ,&nbsp;Salamida Daudi ,&nbsp;Steady Mushayabasa","doi":"10.1016/j.rico.2025.100522","DOIUrl":"10.1016/j.rico.2025.100522","url":null,"abstract":"<div><div>Cassava remains Sub-Saharan Africa’s second most crucial staple food crop after maize. However, production of sufficient yields is hampered by pests and diseases. In particular, the whitefly (<em>Bemisia tabaci</em>) has the potential to reduce expected yields by 50% since it directly damages cassava leaves by feeding on phloem, causing chlorosis and abscission. This study develops a novel mathematical model for cassava mosaic disease that incorporates immature and adult whitefly populations. Additionally, the model includes vector feeding behavior since prior studies have shown that vectors exhibit preferences to settle for either healthy or infected hosts. We determined the offspring number and carried out its sensitivity analysis. Additionally, we carried out an optimal control study on the use of insecticides and plant roguing as disease control measures against cassava mosaic disease. Our results show that vector preference and efficiency of disease control strategies plays an important role in shaping the short and long-term dynamics of cassava mosaic disease, which subsequently impacts the design of its optimal control strategies.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"18 ","pages":"Article 100522"},"PeriodicalIF":0.0,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143176330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sensitivity analysis and uncertainty quantification of climate change effects on Tanzanian banana crop yield","authors":"Sabas Patrick ,&nbsp;Silas Mirau ,&nbsp;Isambi Mbalawata ,&nbsp;Judith Leo","doi":"10.1016/j.rico.2025.100519","DOIUrl":"10.1016/j.rico.2025.100519","url":null,"abstract":"<div><div>Concerns about the impact of climate change on agricultural systems have heightened, particularly in regions where crop cultivation is essential for economic stability and sustenance. This research addresses a critical gap in understanding by investigating how climate change influences Tanzania’s bananas, a vital component of the country’s agricultural sector. The study used a multiple regression model to analyze the correlation between bananas and key climate variables in Tanzania, the results showed gradual decrease in bananas. Specifically, the climate variables, including precipitation (<span><math><msub><mrow><mi>X</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span>), soil moisture (<span><math><msub><mrow><mi>X</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span>), minimum temperature (<span><math><msub><mrow><mi>X</mi></mrow><mrow><mn>3</mn></mrow></msub></math></span>), maximum temperature (<span><math><msub><mrow><mi>X</mi></mrow><mrow><mn>4</mn></mrow></msub></math></span>), and relative humidity (<span><math><msub><mrow><mi>X</mi></mrow><mrow><mn>5</mn></mrow></msub></math></span>) have coefficients 0.0206, −0.0085, 4.8328, −1.6594, and −0.0991, respectively. In this case, a large positive coefficient and a negligible negative coefficient show that the independent variable greatly influences the yield of the bananas. Additionally, the study utilize two powerful global sensitivity analysis methods, Sobol’ Sensitivity Indices and Response Surface Methodology, to comprehensively explore the sensitivity of bananas to climate variables. So, these methods revealed that minimum temperature, precipitation and soil moisture have the most impact on bananas and affect the crop’s production variability. Uncertainty quantification was performed using Monte Carlo simulation, estimating uncertainties in model parameters to enhance the reliability of the findings. This research not only contributes to our broader understanding of how climate change impacts bananas but also offers practical policy suggestions tailored to Tanzania’s unique context, ensuring resilience and sustainability in the face of environmental changes. The outcomes of this study carry significance for policymakers, stakeholders, and farmers, providing actionable insights to shape adaptive agricultural strategies. By bridging the gap between climate change and bananas, this research offers valuable contributions to the broader field of agricultural sustainability.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"18 ","pages":"Article 100519"},"PeriodicalIF":0.0,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143176331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fractional optimal control problem modeling bovine tuberculosis and rabies co-infection","authors":"Boubacar Diallo ,&nbsp;Munkaila Dasumani ,&nbsp;Jeconia Abonyo Okelo ,&nbsp;Shaibu Osman ,&nbsp;Oumar Sow ,&nbsp;Nnaemeka Stanley Aguegboh ,&nbsp;Walter Okongo","doi":"10.1016/j.rico.2025.100523","DOIUrl":"10.1016/j.rico.2025.100523","url":null,"abstract":"<div><div>Bovine tuberculosis (bTB) and rabies are eminent zoonotic afflictions that significantly impact global economic stability and public health, with pronounced effects in developing nations. These diseases continuously pressure public health systems and obstruct efforts to improve livestock productivity and export capabilities. Studying the joint dynamics of bTB and rabies involves notable mathematical complexities due to the differences in their transmission mechanisms. Moreover, while there is some overlap among animal populations at risk for bTB and rabies, the exact proportion of animals susceptible to both diseases remains unspecified. In this work, we provide a simplified fractional-order optimal control model that integrates the dynamics of bTB and rabies co-infection. We determine the basic reproduction numbers for bovine tuberculosis <span><math><mfenced><mrow><msubsup><mrow><mi>R</mi></mrow><mrow><mn>0</mn></mrow><mrow><mi>T</mi></mrow></msubsup></mrow></mfenced></math></span> and rabies <span><math><mrow><mo>(</mo><msubsup><mrow><mi>R</mi></mrow><mrow><mn>0</mn></mrow><mrow><mi>R</mi></mrow></msubsup><mo>)</mo></mrow></math></span>, as well as the overall reproduction number for the model <span><math><mrow><mi>R</mi><mo>=</mo><mo>max</mo><mrow><mo>{</mo><msubsup><mrow><mi>R</mi></mrow><mrow><mn>0</mn></mrow><mrow><mi>T</mi></mrow></msubsup><mo>,</mo><msubsup><mrow><mi>R</mi></mrow><mrow><mn>0</mn></mrow><mrow><mi>R</mi></mrow></msubsup><mo>}</mo></mrow></mrow></math></span>. The qualitative analysis reveals that when <span><math><mrow><mi>R</mi><mo>&lt;</mo><mn>1</mn></mrow></math></span>, the disease-free equilibrium is locally asymptotically stable. We implement optimal control analysis to identify the best strategies for preventing each disease separately and their co-infection. The optimal control problem is solved numerically utilizing a forward–backward predict-evaluate correct-evaluate (PECE) algorithm implemented in Matlab software. The simulation results show that <strong>strategy E</strong> (<span><math><mrow><mi>i</mi><mo>.</mo><mi>e</mi><mo>.</mo></mrow></math></span>, implementation of all optimal controls) is significantly more effective in managing bovine tuberculosis but less effective in controlling rabies and co-infection. Conversely, <strong>strategy B</strong> (<span><math><mrow><mi>i</mi><mo>.</mo><mi>e</mi><mo>.</mo></mrow></math></span>, applying vaccination and removal of optimal controls for animals affected by rabies) provides satisfactory optimal control results across the three infection scenarios.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"18 ","pages":"Article 100523"},"PeriodicalIF":0.0,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143176334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}