Article
Computer Science, Artificial Intelligence
Shubham Pateria, Budhitama Subagdja, Ah-Hwee Tan, Chai Quek
Summary: This article proposes a novel subgoal graph-based planning method called LSGVP, which addresses the challenge of learning to reach long-horizon goals in spatial traversal tasks for autonomous agents. LSGVP uses a subgoal discovery heuristic based on cumulative reward and automatically prunes the learned subgoal graph to remove erroneous connections. It achieves higher cumulative positive rewards and goal-reaching success rates compared to other subgoal sampling or discovery heuristics.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Automation & Control Systems
Xin Wang, Wei Xie, Zhi-Sheng Ye
Summary: This article studies the warranty reserve planning problem for a firm that makes electronic products. By incorporating randomness of product sales and failures, the article analyzes the time-varying behavior of the warranty demand and optimizes the warranty reserve levels.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Robotics
Hoseong Seo, Donggun Lee, Clark Youngdong Son, Inkyu Jang, Claire J. Tomlin, H. Jin Kim
Summary: This article presents a real-time receding-horizon robust trajectory planning algorithm for nonlinear closed-loop systems, which guarantees the safety of the system under unknown but bounded disturbances. The proposed method enables real-time replanning of a reference trajectory with safety guarantees even when the system encounters unexpected disturbances in runtime.
IEEE TRANSACTIONS ON ROBOTICS
(2023)
Article
Automation & Control Systems
Xueyang Yang, Zhiyong Yu
Summary: This paper investigates a class of coupled forward-backward stochastic differential equations (FBSDEs) on infinite horizon involving time delays and time advancements, and achieves the unique solvability by introducing a randomized Lipschitz condition and a randomized monotonicity condition. The theoretical result is then applied to a linear-quadratic problem of a time-delayed system with random coefficients, leading to an explicit expression of the unique optimal control.
SYSTEMS & CONTROL LETTERS
(2022)
Article
Computer Science, Artificial Intelligence
Pei-Yi Hao
Summary: This article introduces a novel asymmetric dual-regression model that combines twin-support vector machine theory with the principles of possibilistic regression analysis, providing better modeling of data distribution and confidence measure for predicted outputs. The proposed approach efficiently solves multiple smaller problems during training, leading to reduced time cost.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Shiqing Gao, Haibo Shi, Fang Wang, Zijian Wang, Siyu Zhang, Yunxia Li, Yaoru Sun
Summary: This paper presents a model-based deterministic policy gradient (MBDPG) method for efficient utilization of learned dynamics models through multi-step gradient information. It demonstrates higher sampling efficiency and convergence performance compared to the state-of-the-art model-based reinforcement learning methods.
Article
Automation & Control Systems
Matteo Basei, Xin Guo, Anran Hu, Yufei Zhang
Summary: This paper studies finite-time horizon continuous-time linear-quadratic reinforcement learning problems. A least-squares algorithm based on continuous-time observations and controls is proposed and a logarithmic regret bound is established. Furthermore, a practically implementable least-squares algorithm based on discrete-time observations and piecewise constant controls is introduced.
JOURNAL OF MACHINE LEARNING RESEARCH
(2022)
Article
Engineering, Biomedical
Doran Wood, Sila Cetinkaya, Harsha Gangammanavar, Weigo Lu, Jing Wang
Summary: This study aims to develop optimization models and methods that adapt treatment decisions across multiple fractions by utilizing predictions of tumor evolution. By introducing a nonuniform allocation scheme, we demonstrate the superiority of this approach across multiple performance metrics.
PHYSICS IN MEDICINE AND BIOLOGY
(2022)
Article
Computer Science, Artificial Intelligence
Anushri Dixit, Mohamadreza Ahmadi, Joel W. Burdick
Summary: This paper investigates the problem of risk-averse receding horizon motion planning for agents with uncertain dynamics in the presence of stochastic, dynamic obstacles. The proposed model predictive control (MPC) scheme formulates the obstacle avoidance constraint using coherent risk measures. A waypoint following algorithm using the MPC scheme is also proposed and proved to be risk-sensitive and recursively feasible while guaranteeing finite-time task completion. The paper further explores commonly used coherent risk metrics and proposes a tractable incorporation within MPC. Simulation studies are conducted to illustrate the framework.
ARTIFICIAL INTELLIGENCE
(2023)
Article
Mathematics
Dragos-Patru Covei
Summary: This article focuses on a stochastic production planning problem with regime switching, aiming to minimize production costs through the value function approach. The main contribution is the identification of an exact solution of an elliptic system of partial differential equations that characterizes the optimal production. A verification result is provided for the determined solution.
Article
Mathematics, Applied
Naoyuki Ichihara
Summary: This paper examines the asymptotic behavior of value functions for finite horizon countable state Markov decision processes with an absorbing set as a constraint. It is found that the value function exhibits three different limiting behaviors based on the critical value lambda(*), namely converging to a solution of the stationary equation, approaching a solution of the ergodic problem after normalization, or diverging to infinity at most with a logarithmic order. These results are used to investigate qualitative properties of the optimal Markovian policy for a finite horizon MDP with a sufficiently large time horizon.
APPLIED MATHEMATICS AND OPTIMIZATION
(2021)
Article
Operations Research & Management Science
Chonghu Guan, Zuo Quan Xu, Rui Zhou
Summary: This paper examines a dynamic optimal reinsurance and dividend-payout problem for an insurance company in a finite time horizon. By establishing a mathematical model and computational methods, the study determines the optimal strategies for the insurance company at different surplus levels, and provides estimates for the corresponding risk and dividend-payout levels.
MATHEMATICS OF OPERATIONS RESEARCH
(2022)
Article
Mathematics, Applied
Jiangyan Pu, Qi Zhang
Summary: This paper studies a control-constrained stochastic LQ optimal control problem with random coefficients on the infinite time horizon, introducing two generalized infinite time horizon stochastic Riccati equations to provide explicit optimal control and cost solutions. The application of this study is demonstrated through the control problem of a pension fund with a DB scheme.
APPLIED MATHEMATICS AND OPTIMIZATION
(2021)
Article
Engineering, Chemical
Chaoyue Ma, Ting Hou
Summary: This paper deals with the H-2/H-infinity control problem in the infinite horizon for discrete-time mean-field stochastic systems with (x, u, v)-dependent noise. A stochastic-bounded real lemma is derived as the core of H-infinity analysis. A sufficient condition in terms of the solution of coupled difference Riccati equations (CDREs) is obtained for solving the control problem. An iterative algorithm for solving CDREs is proposed and a numerical example is given for verification of the feasibility of the developed results.
Article
Computer Science, Hardware & Architecture
Alice Consilvio, Angela Di Febbraro, Nicola Sacco
Summary: This article proposes a risk-based scheduling model for predictive maintenance activities on a railway line, taking into account the stochastic nature of real environments and introducing a rolling-horizon framework for dynamic adjustment of maintenance plans. The model, formulated as a mixed-integer linear programming problem based on risk minimization and adhering to ISO 55 000 guidelines, allows for day-to-day planning and adaptation to real-time information in a real rail network scenario, with a focus on tamping activities at the operational level.
IEEE TRANSACTIONS ON RELIABILITY
(2021)
Article
Computer Science, Artificial Intelligence
Aditi Khanra, Tandra Pal, Manas Kumar Maiti, Manoranjan Maiti
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2019)
Article
Computer Science, Artificial Intelligence
Nilesh Pakhira, Manas Kumar Maiti, Manoranjan Maiti
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2019)
Article
Computer Science, Artificial Intelligence
Indadul Khan, Soya Pal, Manas Kumar Maiti
INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS
(2019)
Article
Computer Science, Artificial Intelligence
Prasenjit Pramanik, Manas Kumar Maiti
Article
Computer Science, Artificial Intelligence
Mostafijur Rahaman, Sankar Prasad Mondal, Ali Akbar Shaikh, Prasenjit Pramanik, Samarjit Roy, Manas Kumar Maiti, Rituparna Mondal, Debashis De
Article
Computer Science, Artificial Intelligence
Indadul Khan, Manas Kumar Maiti, Krishnendu Basuli
APPLIED INTELLIGENCE
(2020)
Article
Computer Science, Artificial Intelligence
Indadul Khan, Manas Kumar Maiti, Krishnendu Basuli
Summary: A novel heuristic algorithm, combining random-permutation technique and genetic algorithm, is proposed for solving generalized travelling salesman problem. The algorithm can handle both crisp and imprecise environments, and has achieved promising results in experiments.
EVOLUTIONARY INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Indadul Khan, Manas Kumar Maiti, Krishnendu Basuli
Summary: Using shuffle, re-generation, and 4-opt operation, a novel heuristic is proposed for the multi-objective generalized traveling salesman problems. The algorithm utilizes a three-layer solution updating mechanism and achieves improved performance compared to other heuristics.
APPLIED INTELLIGENCE
(2022)
Article
Computer Science, Artificial Intelligence
Prasanta Dutta, Indadul Khan, Krishnendu Basuli, Manas Kumar Maiti
Summary: In this study, the ant colony optimization (ACO) algorithm is modified with the K-Opt operation to solve the covering salesman problem (CSP) under crisp and imprecise environments. The proposed algorithm finds the shortest path while considering the specified coverage range. It also addresses the challenges of dealing with imprecise data and provides simulation approaches for solving CSPs.
Article
Computer Science, Artificial Intelligence
Indadul Khan, Krishnendu Basuli, Manas Kumar Maiti
Summary: In this study, the basic Grey Wolf Optimization (GWO) algorithm is modified and integrated with the Multi-Objective Evolutionary Algorithm with Decomposition (MOEA/D) to solve the Multi-Objective Covering Salesman Problem (MOCSP). A two-phase algorithm is proposed, which involves clustering the cities and then selecting cities from each cluster to search for Pareto-optimal Hamiltonian cycles. The algorithm is tested on different benchmark instances and compared with other traditional multi-objective optimization algorithms. The results show that the proposed algorithm is efficient in dealing with MOCSP.
KNOWLEDGE AND INFORMATION SYSTEMS
(2023)
Article
Operations Research & Management Science
Pravash Kumar Giri, Manas Kumar Maiti, Manoranjan Maiti
Summary: This research utilizes the concept of breakable substitute items and budget constraints in decision-making problems. The problem of breakable substitute items is considered under a fuzzy environment in a fixed charge multi-item four-dimensional transportation problem (4D-TP) with profit maximization as the objective. The problem involves purchasing items from different depots at different prices and delivering different types of items to separate destinations using different types or capacities of vehicles. Fuzzy constraints are transformed into equivalent deterministic constraints using credibility measures, and the reduced fuzzy optimization problem is solved using swap-based particle swarm optimization (SPSO) and credibility-based genetic algorithm (CBGA). The results obtained from CBGA and SPSO for 4D-TP are compared, and the paper also presents results from solid transportation problems (3D-TPs) and conventional transportation problems (2D-TPs) for demonstration, with statistical analysis performed to compare the algorithms.
Article
Engineering, Industrial
Nilesh Pakhira, Manas Kumar Maiti, Manoranjan Maiti
Summary: A multi-item two-level supply chain model under promotional cost sharing is proposed and analysed, where a retailer purchases items from a wholesaler and sells to customers using two rented warehouses. The model considers factors such as displayed inventory levels, selling prices, and frequencies of advertisements to determine demands. The problem is formulated as a mixed-integer optimization problem and solved using a modified artificial bee colony algorithm. Illustrative examples and managerial insights are provided to demonstrate the model's applicability in real-life scenarios.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE-OPERATIONS & LOGISTICS
(2021)
Article
Mathematics, Applied
N. Pakhira, M. K. Maiti, M. Maiti
IRANIAN JOURNAL OF FUZZY SYSTEMS
(2020)
Article
Engineering, Industrial
Prasenjit Pramanik, Manas Kumar Maiti
EUROPEAN JOURNAL OF INDUSTRIAL ENGINEERING
(2019)
Article
Engineering, Multidisciplinary
Prasenjit Pramanik, Sarama Malik Das, Manas Kumar Maiti
JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION
(2019)
Article
Engineering, Multidisciplinary
A. A. Aganin, A. I. Davletshin
Summary: A mathematical model of interaction of weakly non-spherical gas bubbles in liquid is proposed in this paper. The model equations are more accurate and compact compared to existing analogs. Five problems are considered for validation, and the results show good agreement with experimental data and numerical solutions. The model is also used to analyze the behavior of bubbles in different clusters, providing meaningful insights.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Hao Wu, Jie Sun, Wen Peng, Lei Jin, Dianhua Zhang
Summary: This study establishes an analytical model for the coupling of temperature, deformation, and residual stress to explore the mechanism of residual stress formation in hot-rolled strip and how to control it. The accuracy of the model is verified by comparing it with a finite element model, and a method to calculate the critical exit crown ratio to maintain strip flatness is proposed.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Shengwen Tu, Naoki Morita, Tsutomu Fukui, Kazuki Shibanuma
Summary: This study aimed to extend the finite element method to cope with elastic-plastic problems by introducing the s-version FEM. The s-version FEM, which overlays a set of local mesh with fine element size on the conventional FE mesh, simplifies domain discretisation and provides accurate numerical predictions. Previous applications of the s-version FEM were limited to elastic problems, lacking instructions for stress update in plasticity. This study presents detailed instructions and formulations for addressing plasticity problems with the s-version FEM and analyzes a stress concentration problem with linear/nonlinear material properties.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Bo Fan, Zhongmin Wang
Summary: A 3D rotating hyperelastic composite REF model was proposed to analyze the influence of tread structure and rotating angular speed on the vibration characteristics of radial tire. Nonlinear dynamic differential equations and modal equations were established to study the effects of internal pressure, tread pressure sharing ratio, belt structure, and rotating angular speed on the vibration characteristics.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
X. W. Chen, Z. Q. Yue, Wendal Victor Yue
Summary: This paper examines the axisymmetric problem of a flat mixed-mode annular crack near and parallel to an arbitrarily graded interface in functionally graded materials (FGMs). The crack is modeled as plane circular dislocation loop and an efficient solution for dislocation in FGMs is used to calculate the stress field at the crack plane. The analytical solutions of the stress intensity factors are obtained and numerical study is conducted to investigate the fracture mechanics of annular crack in FGMs.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Xumin Guo, Jianfei Gu, Hui Li, Kaihua Sun, Xin Wang, Bingjie Zhang, Rangwei Zhang, Dongwu Gao, Junzhe Lin, Bo Wang, Zhong Luo, Wei Sun, Hui Ma
Summary: In this study, a novel approach combining the transfer matrix method and lumped parameter method is proposed to analyze the vibration response of aero-engine pipelines under base harmonic and random excitations. The characteristics of the pipelines are investigated through simulation and experiments, validating the effectiveness of the proposed method.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Xiangyu Sha, Aizhong Lu, Ning Zhang
Summary: This paper investigates the stress and displacement of a layered soil with a fractional-order viscoelastic model under time-varying loads. The correctness of the solutions is validated using numerical methods and comparison with existing literature. The research findings are of significant importance for exploring soil behavior and its engineering applications under time-varying loads.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Thuy Dong Dang, Thi Kieu My Do, Minh Duc Vu, Ngoc Ly Le, Tho Hung Vu, Hoai Nam Vu
Summary: This paper investigates the nonlinear torsional buckling of corrugated core sandwich toroidal shell segments with functionally graded graphene-reinforced composite (FG-GRC) laminated coatings in temperature change using the Ritz energy method. The results show the significant beneficial effects of FG-GRC laminated coatings and corrugated core on the nonlinear buckling responses of structures.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Zhihao Zhai, Chengbiao Cai, Qinglai Zhang, Shengyang Zhu
Summary: This paper investigates the effect of localized cracks induced by environmental factors on the dynamic performance and service life of ballastless track in high-speed railways. A mathematical approach for forced vibrations of Mindlin plates with a side crack is derived and implemented into a train-track coupled dynamic system. The accuracy of this approach is verified by comparing with simulation and experimental results, and the dynamic behavior of the side crack under different conditions is analyzed.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
James Vidler, Andrei Kotousov, Ching-Tai Ng
Summary: The far-field methodology, developed by J.C. Maxwell, is utilized to estimate the effective third order elastic constants of composite media containing random distribution of spherical particles. The results agree with previous studies and can be applied to homogenization problems in other fields.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Kim Q. Tran, Tien-Dat Hoang, Jaehong Lee, H. Nguyen-Xuan
Summary: This study presents novel frameworks for graphene platelets reinforced functionally graded triply periodic minimal surface (GPLR-FG-TPMS) plates and investigates their performance through static and free vibration analyses. The results show that the mass density framework has potential for comparing different porous cores and provides a low weight and high stiffness-to-weight ratio. Primitive plates exhibit superior performance among thick plates.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Bence Hauck, Andras Szekrenyes
Summary: This study explores several methods for computing the J-integral in laminated composite plate structures with delamination. It introduces two special types of plate finite elements and a numerical algorithm. The study presents compact formulations for calculating the J-integral and applies matrix multiplication to take advantage of plate transition elements. The models and algorithms are applied to case studies and compared with analytical and previously used finite element solutions.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Wu Ce Xing, Jiaxing Wang, Yan Qing Wang
Summary: This paper proposes an effective mathematical model for bolted flange joints to study their vibration characteristics. By modeling the flange and bolted joints, governing equations are derived. Experimental studies confirm that the model can accurately predict the vibration characteristics of multiple-plate structures.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Pingchao Yu, Li Hou, Ke Jiang, Zihan Jiang, Xuanjun Tao
Summary: This paper investigates the imbalance problem in rotating machinery and finds that mass imbalance can induce lateral-torsional coupling vibration. By developing a model and conducting detailed analysis, it is discovered that mass imbalance leads to nonlinear time-varying characteristics and there is no steady-state torsional vibration in small unbalanced rotors. Under largely unbalanced conditions, both resonant and unstable behavior can be observed, and increasing lateral damping can suppress instability and reduce lateral amplitude in the resonance region.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Yong Cao, Ziwen Guo, Yilin Qu
Summary: This paper investigates the mechanically induced electric potential and charge redistribution in a piezoelectric semiconductor cylindrical shell. The results show that doping levels can affect the electric potentials and mechanical displacements, and alter the peak position of the zeroth-order electric potential. The doping level also has an inhibiting effect on the first natural frequency. These findings are crucial for optimizing the design and performance of cylindrical shell-shaped sensors and energy harvesters.
APPLIED MATHEMATICAL MODELLING
(2024)
