Relevant bibliographies by topics / Epsilon constraint method

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Epsilon constraint method'

Author: Grafiati
Published: 11 December 2022
Last updated: 25 May 2024

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Journal articles on the topic "Epsilon constraint method"

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Pérez‐Cañedo, Boris, José Luis Verdegay, and Ridelio Miranda Pérez. "An epsilon‐constraint method for fully fuzzy multiobjective linear programming." International Journal of Intelligent Systems 35, no. 4 (January 12, 2020): 600–624. http://dx.doi.org/10.1002/int.22219.

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Kai, Liu, and Ramina Malekalipour Kordestanizadeh. "Designing an Agile Closed-Loop Supply Chain with Environmental Aspects Using a Novel Multiobjective Metaheuristic Algorithm." Mathematical Problems in Engineering 2021 (November 2, 2021): 1–13. http://dx.doi.org/10.1155/2021/3811417.

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Success in supply chain implementation depends on the way of dealing with market changes and customer needs. Agility is a concept that has been introduced in recent years to improve the supply chain. On the other hand, paying attention to environmental problems is another issue, and chains are trying to increase their popularity by focusing on this issue. Considering the importance of this issue, designing a multiobjective closed-loop supply chain network has been discussed in this research. The main contribution of this research is the integration of green and agility concepts in supply chain design. In this regard, a mathematical model is presented with economic, environmental, and agility objectives. First, the mathematical model is solved using the Epsilon constraint method, and then, the multiobjective weed algorithm is proposed to solve the model. The results of comparisons between the two methods show that the multiobjective weed algorithm has performed well in terms of various metrics of NPS, SNS, and Max Spread. In terms of the solving time, the average solving time of this algorithm was about 0.1% of the solving time of the Epsilon constraint method. Moreover, all cases show the superiority of the multiobjective weed algorithm over the Epsilon constraint method in solving the proposed mathematical model.
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Zhou, Jinlong, Juan Zou, Jinhua Zheng, Shengxiang Yang, Dunwei Gong, and Tingrui Pei. "An infeasible solutions diversity maintenance epsilon constraint handling method for evolutionary constrained multiobjective optimization." Soft Computing 25, no. 13 (May 25, 2021): 8051–62. http://dx.doi.org/10.1007/s00500-021-05880-5.

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Agud-Albesa, Lucia, Neus Garrido, Angel A. Juan, Almudena Llorens, and Sandra Oltra-Crespo. "A Weighted and Epsilon-Constraint Biased-Randomized Algorithm for the Biobjective TOP with Prioritized Nodes." Computation 12, no. 4 (April 20, 2024): 84. http://dx.doi.org/10.3390/computation12040084.

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This paper addresses a multiobjective version of the Team Orienteering Problem (TOP). The TOP focuses on selecting a subset of customers for maximum rewards while considering time and fleet size constraints. This study extends the TOP by considering two objectives: maximizing total rewards from customer visits and maximizing visits to prioritized nodes. The MultiObjective TOP (MO-TOP) is formulated mathematically to concurrently tackle these objectives. A multistart biased-randomized algorithm is proposed to solve MO-TOP, integrating exploration and exploitation techniques. The algorithm employs a constructive heuristic defining biefficiency to select edges for routing plans. Through iterative exploration from various starting points, the algorithm converges to high-quality solutions. The Pareto frontier for the MO-TOP is generated using the weighted method, epsilon-constraint method, and Epsilon-Modified Method. Computational experiments validate the proposed approach’s effectiveness, illustrating its ability to generate diverse and high-quality solutions on the Pareto frontier. The algorithms demonstrate the ability to optimize rewards and prioritize node visits, offering valuable insights for real-world decision making in team orienteering applications.
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Mavalizadeh, Hani, and Abdollah Ahmadi. "Hybrid expansion planning considering security and emission by augmented epsilon-constraint method." International Journal of Electrical Power & Energy Systems 61 (October 2014): 90–100. http://dx.doi.org/10.1016/j.ijepes.2014.03.004.

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Jin, Bangti, Buyang Li, and Zhi Zhou. "Pointwise-in-time error estimates for an optimal control problem with subdiffusion constraint." IMA Journal of Numerical Analysis 40, no. 1 (October 30, 2018): 377–404. http://dx.doi.org/10.1093/imanum/dry064.

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Abstract In this work we present numerical analysis for a distributed optimal control problem, with box constraint on the control, governed by a subdiffusion equation that involves a fractional derivative of order $\alpha \in (0,1)$ in time. The fully discrete scheme is obtained by applying the conforming linear Galerkin finite element method in space, L1 scheme/backward Euler convolution quadrature in time, and the control variable by a variational-type discretization. With a space mesh size $h$ and time stepsize $\tau $ we establish the following order of convergence for the numerical solutions of the optimal control problem: $O(\tau ^{\min ({1}/{2}+\alpha -\epsilon ,1)}+h^2)$ in the discrete $L^2(0,T;L^2(\varOmega ))$ norm and $O(\tau ^{\alpha -\epsilon }+\ell _h^2h^2)$ in the discrete $L^{\infty }(0,T;L^2(\varOmega ))$ norm, with any small $\epsilon>0$ and $\ell _h=\ln (2+1/h)$. The analysis relies essentially on the maximal $L^p$-regularity and its discrete analogue for the subdiffusion problem. Numerical experiments are provided to support the theoretical results.
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Tartibu, L. K., B. Sun, and M. A. E. Kaunda. "Optimal design study of thermoacoustic regenerator with lexicographic optimization method." Journal of Engineering, Design and Technology 13, no. 3 (July 6, 2015): 499–519. http://dx.doi.org/10.1108/jedt-09-2012-0039.

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Purpose – This paper aims to illustrate the use of the augmented epsilon-constraint method implemented in general algebraic modelling system (GAMS), aimed at optimizing the geometry of a thermoacoustic regenerator. Thermoacoustic heat engines provide a practical solution to the problem of heat management where heat can be pumped or spot cooling can be produced. However, the most inhibiting characteristic of thermoacoustic cooling is their current lack of efficiencies. Design/methodology/approach – Lexicographic optimization is presented as an alternative optimization technique to the common used weighting methods. This approach establishes a hierarchical order among all the optimization objectives instead of giving them a specific (and most of the time, arbitrary) weight. Findings – A practical example is given, in a hypothetical scenario, showing how the proposed optimization technique may help thermoacoustic regenerator designers to identify Pareto optimal solutions when dealing with geometric parameters. This study highlights the fact that the geometrical parameters are interdependent, which support the use of a multi-objective approach for optimization in thermoacoustic. Originality/value – The research output from this paper can be a valuable resource to support designers in building efficient thermoacoustic device. The research illustrates the use of a lexicographic optimization to provide more meaningful results describing the geometry of thermoacoustic regenerator. It applies the epsilon-constraint method (AUGMENCON) to solve a five-criteria mixed integer non-linear problem implemented in GAMS (GAM software).
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Estrin, Ron, and Michael P. Friedlander. "A perturbation view of level-set methods for convex optimization." Optimization Letters 14, no. 8 (June 12, 2020): 1989–2006. http://dx.doi.org/10.1007/s11590-020-01609-9.

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Abstract Level-set methods for convex optimization are predicated on the idea that certain problems can be parameterized so that their solutions can be recovered as the limiting process of a root-finding procedure. This idea emerges time and again across a range of algorithms for convex problems. Here we demonstrate that strong duality is a necessary condition for the level-set approach to succeed. In the absence of strong duality, the level-set method identifies $$\epsilon $$ ϵ -infeasible points that do not converge to a feasible point as $$\epsilon $$ ϵ tends to zero. The level-set approach is also used as a proof technique for establishing sufficient conditions for strong duality that are different from Slater’s constraint qualification.
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Bamogo, W., K. Some, and G. A. Degla. "PERFORMANCE STUDY OF MULTIOBJECTIVE OPTIMIZER METHOD BASED ON GREY WOLF ATTACK TECHNICS." Journal of Computer Science and Applied Mathematics 5, no. 2 (September 30, 2023): 53——73. http://dx.doi.org/10.37418/jcsam.5.2.2.

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This paper proposes a performance study for the Multiobjective Optimizer based on the Grey Wolf Attack technics (MOGWAT). It is a method of solving multiobjective optimization problems. The method consists of the resolution of an unconstrained single objective optimization problem, which is derived from the aggregation of objective functions by the $\epsilon$-constraint approach and the penalization of constraints by a Lagrangian function. Then, Pareto-optimal solutions are obtained using the stochastic method based on the Grey Wolf Optimizer. To evaluate the method, three theorems have been formulated to demonstrate the convergence of the proposed algorithm and the optimality of the obtained solutions. Six test problems from the literature have been successfully dealt with, and the obtained results have been compared to two other methods. We have evaluated two performance parameters, including the generational distance for the approximation error and the spread for the coverage of the Pareto front. Based on these numerical findings, it can be concluded that MOGWAT outperforms two other methods.
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Bozoklar, Emine, and Ebru Yılmaz. "Designing Sustainable Flexible Manufacturing Cells with Multi-Objective Optimization Models." Applied Sciences 14, no. 1 (December 25, 2023): 203. http://dx.doi.org/10.3390/app14010203.

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Having sustainable and flexible features is crucial for manufacturing companies considering the increasing competition in the globalized world. This study considers three aspects of sustainability, namely economic, social, and environmental factors, in the design of flexible manufacturing cells. Three different multi-objective integer mathematical programming models were developed with the objective of minimizing the costs associated with carbon emissions, inter-cellular movements, machine processing, machine replacement, worker training, and additional salary (bonus). Simultaneously, these models aim to minimize the carbon emission amount of the cells within the environmental dimension scope. The developed models are a goal programming model, an epsilon constraint method, and an augmented epsilon constraint (AUGMECON) method. In these models, alternative routes of parts are considered while assigning parts to machines. The results are obtained using the LINGO 20.0 optimization program with a developed illustrative example. The obtained results are tested and compared by performing sensitivity analyses. The sensitivity analyses include examinations of the effects of changes in part demands, machine capacity values, carbon limit value, and the maximum number of workers in cells.
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Dissertations / Theses on the topic "Epsilon constraint method"

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Bevrani, Bayan. "Multi-criteria capacity assessment and planning models for multi-modal transportation systems." Thesis, Queensland University of Technology, 2018. https://eprints.qut.edu.au/122895/1/Bayan_Bevrani_Thesis.pdf.

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This research provides a comprehensive set of methods for the capacity assessment of multi-modal transportation systems, which are easy to apply and can significantly reduce the time to perform a capacity analysis. This thesis developed multi-objective mathematical models that can evaluate the effect of parametric and structural changes and can assist planners to update and reconfigure multi-modal transportation systems considering the trade-off in different aspects of cost, time and functionality. The methods proposed in this thesis can help planners and decision-makers to identify the performance and capability of multiple modes of an integrated transportation system.
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Gao, Liping. "Efficient approaches for large-scale time-dependent route planning problems with traveler's preference." Electronic Thesis or Diss., université Paris-Saclay, 2023. https://www.biblio.univ-evry.fr/theses/2023/interne/2023UPASG084.pdf.

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La planification d'itinéraires en fonction du temps dans les réseaux du monde réel reste aujourd'hui un défi majeur. De plus, les voyageurs peuvent avoir simultanément de multiples préférences telles que le temps de trajet, la beauté des paysages, la sécurité et les faibles émissions de carbone. Avec le développement des infrastructures et les progrès des technologies de l'information, diverses données spatio-temporelles qui enregistrent les interactions entre les humains et le monde cyber-physique peuvent être collectées et utilisées pour concevoir la planification d'itinéraires en fonction des préférences des voyageurs. Cependant, la plupart des recherches se concentrent sur la recherche du chemin le plus court dans un réseau dépendant du temps. En particulier, 1) certains travaux se concentrent sur l'optimisation du score de préférence total du voyageur, mais proposent uniquement un modèle non linéaire qui ne peut être abordé efficacement ; 2) peu de travaux étudient les problèmes de planification d'itinéraires multi-objectifs dépendant du temps, dans lesquels le score de préférence du voyageur est supposé in- changé. Cependant, les préférences du voyageur peuvent varier avec le temps ; 3) des travaux récents étudient les problèmes de planification d'itinéraires axés sur les groupes, mais considèrent que le temps de trajet et les préférences des voyageurs ne varient pas dans le temps. Afin de réduire les écarts entre la théorie et la pratique, trois nouveaux problèmes de planification d'itinéraires dépendant du temps en prenant compte des préférences du voyageur (TRPPs-TP) sont étudiés dans cette thèse.Premièrement, un TRPP-TP à objectif unique est étudié dans la mesure où le score de préférence sur les segments routiers est supposé dépendre du temps. L'objectif est de maximiser le score de préférence total. Pour le problème, un modèle de programmation linéaire en nombres entiers est proposé et la complexité NP-difficile du problème est analysée. Pour résoudre le problème efficacement, une nouvelle méthode en deux phases est développée. Des expériences numériques sur des réseaux routiers générés aléatoirement et sur des réseaux routiers réels démontrent la supériorité de la méthode développée.Deuxièmement, un TRPP-TP bi-objectif avec un score de préférence dépendant du temps est étudié. Le premier objectif est de maximiser le score de préférence total, et le second est de minimiser le temps de trajet total. Pour résoudre ce problème, un modèle de programmation linéaire en nombres entiers est formulé. Pour résoudre le problème, une méthode de epsilon-contrainte exacte est appliquée pour trouver le front de Pareto sur des instances de petite taille. Pour gérer des instances de grande taille, un algorithme génétique de tri non dominé spécifique à un problème-II (NSGA-II) est développé. En particulier, un nouveau codage basé sur la région est conçu et une condition d'itinéraire réalisable est fournie pour trouver des solutions quasi optimales dans un temps de calcul raisonnable. Des expériences sur des réseaux routiers générés aléatoirement et sur des réseaux routiers réels démontrent les performances du NSGA-II proposé.Enfin, un TRPP-TP bi-objectif éco-responsable et orienté groupe est abordé. Le premier objec- tif est de maximiser le score total de préférence des voyageurs et le second est de minimiser les émissions totales de CO2. Pour ce problème, un nouveau modèle de programmation linéaire en nombres entiers est proposé, et une méthode de epsilon-contrainte est utilisée. Des expérimentations numériques sur des réseaux routiers générés aléatoirement sont menées afin de trouver les meilleures solutions d'équilibrage
Time-dependent route planning in real-world networks is still a big challenge today. In addition, travelers may have multi-preferences such as travel time, beautiful scenery, safety, and low carbon, simultaneously. With the development of infrastructures and the advancement of information technology, various spatio-temporal data that record the interactions between humans and the cyber-physical world can be collected and used to design traveler's preference-driven route planning. However, most of research focuses on finding the shortest path in a time-dependent network. In particular, 1) some works focus on optimizing the total traveler's preference score, but only propose a non-linear model that cannot be efficiently addressed; 2) few works investigate multi-objective time-dependent route planning problems, in which traveler preference score is assumed to be unvarying. However, traveler preference can vary with time; 3) recent works study group-oriented route planning problems, but consider the travel time and traveler preference to be time-unvarying. To reduce theory and practice gaps, three new time-dependent route planning problems with traveler's preference (TRPPs-TP) are investigated in this thesis.Firstly, a single-objective TRPP-TP is investigated in that the preference score on road segments is assumed to be time-dependent. The objective is to maximize the total preference score. For the problem, an integer linear programming model is proposed, and the NP-hard complexity of the problem is analyzed. To address the problem efficiently, a novel two-phase method is developed. Numerical experiments on randomly generated road networks and real-world road networks demonstrate the superiority of the developed method.Secondly, a bi-objective TRPP-TP with the time-dependent preference score is studied. The first objective is to maximize the total preference score, and the second one is to minimize the total travel time. For the problem, an integer linear programming model is formulated. For the problem, an exact epsilon-constraint method is applied to find the Pareto front on small-sized instances. To handle large-sized instances, an efficient problem-specific non-dominated sorting genetic algorithm-II (NSGA-II) is developed. Especially, a new region-based coding is designed and a feasible route condition is provided to find near-optimal solutions in a reasonable computation time. Experiments on randomly generated road networks and real-world road networks demonstrate the performance of the proposed NSGA-II.Finally, a bi-objective eco-friendly group-oriented TRPP-TP is addressed. The first objective is to maximize the total traveler preference score and the second one is to minimize the total CO2 emissions. For this problem, a new integer linear programming model is proposed, and an epsilon-constraint method is used. Numerical experiments on randomly generated road networks are conducted to find the best balancing solutions
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(5930024), Kshitij Mall. "Advancing Optimal Control Theory Using Trigonometry For Solving Complex Aerospace Problems." Thesis, 2019.

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Optimal control theory (OCT) exists since the 1950s. However, with the advent of modern computers, the design community delegated the task of solving the optimal control problems (OCPs) largely to computationally intensive direct methods instead of methods that use OCT. Some recent work showed that solvers using OCT could leverage parallel computing resources for faster execution. The need for near real-time, high quality solutions for OCPs has therefore renewed interest in OCT in the design community. However, certain challenges still exist that prohibits its use for solving complex practical aerospace problems, such as landing human-class payloads safely on Mars.

In order to advance OCT, this thesis introduces Epsilon-Trig regularization method to simply and efficiently solve bang-bang and singular control problems. The Epsilon-Trig method resolves the issues pertaining to the traditional smoothing regularization method. Some benchmark problems from the literature including the Van Der Pol oscillator, the boat problem, and the Goddard rocket problem verified and validated the Epsilon-Trig regularization method using GPOPS-II.

This study also presents and develops the usage of trigonometry for incorporating control bounds and mixed state-control constraints into OCPs and terms it as Trigonometrization. Results from literature and GPOPS-II verified and validated the Trigonometrization technique using certain benchmark OCPs. Unlike traditional OCT, Trigonometrization converts the constrained OCP into a two-point boundary value problem rather than a multi-point boundary value problem, significantly reducing the computational effort required to formulate and solve it. This work uses Trigonometrization to solve some complex aerospace problems including prompt global strike, noise-minimization for general aviation, shuttle re-entry problem, and the g-load constraint problem for an impactor. Future work for this thesis includes the development of the Trigonometrization technique for OCPs with pure state constraints.
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Book chapters on the topic "Epsilon constraint method"

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Dahmani, Nadia, Saoussen Krichen, El-Ghazali Talbi, and Sanaa Kaddoura. "Solving the Multi-objective 2-Dimensional Vector Packing Problem Using $$\epsilon $$-constraint Method." In Advances in Intelligent Systems and Computing, 96–104. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72654-6_10.

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Fan, Zhun, Zhi Yang, Yajuan Tang, Wenji Li, Biao Xu, Zhaojun Wang, Fuzan Sun, Zhoubin Long, and Guijie Zhu. "An Improved Epsilon Method with M2M for Solving Imbalanced CMOPs with Simultaneous Convergence-Hard and Diversity-Hard Constraints." In Lecture Notes in Computer Science, 248–56. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72062-9_20.

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Minoli, Daniel, and Benedict Occhiogrosso. "Constrained Average Design Method for QoS-Based Traffic Engineering at the Edge/Gateway Boundary in VANETs and Cyber-Physical Environments." In Managing Resources for Futuristic Wireless Networks, 98–120. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-5225-9493-2.ch005.

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Cyber physical systems (CPSs) are software-intensive smart distributed systems that support physical components endowed with integrated computational capabilities. Tiered, often wireless, networks are typically used to collect or push the data generated or required by a distributed set of CPS-based devices. The edge-to-core traffic flows on the tiered networks can become overwhelming. Thus, appropriate traffic engineering (TE) algorithms are required to manage the flows, while at the same time meeting the delivery requirements in terms of latency, jitter, and packet loss. This chapter provides a basic overview of CPSs followed by a discussion of a newly developed TE method called ‘constrained average', where traffic is by design allowed to be delayed up to a specified, but small value epsilon, but with zero packet loss.
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Conference papers on the topic "Epsilon constraint method"

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Cooper, Kyle, Susan R. Hunter, and Kalyani Nagaraj. "An epsilon-constraint method for integer-ordered bi-objective simulation optimization." In 2017 Winter Simulation Conference (WSC). IEEE, 2017. http://dx.doi.org/10.1109/wsc.2017.8247961.

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Fan, Zhun, Hui Li, Caimin Wei, Wenji Li, Han Huang, Xinye Cai, and Zhaoquan Cai. "An improved epsilon constraint handling method embedded in MOEA/D for constrained multi-objective optimization problems." In 2016 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, 2016. http://dx.doi.org/10.1109/ssci.2016.7850224.

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Javadi, Mohammad, Mohamed Lotfi, Gerardo J. Osorio, Abdelrahman Ashraf, Ali Esmaeel Nezhad, Matthew Gough, and Joao P. S. Catalao. "A Multi-Objective Model for Home Energy Management System Self-Scheduling using the Epsilon-Constraint Method." In 2020 IEEE 14th International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG). IEEE, 2020. http://dx.doi.org/10.1109/cpe-powereng48600.2020.9161526.

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Tartibu, L. K., and M. O. Okwu. "Optimization of a Manifold Microchannel Heat Sink Using an Improved Version of the Augmented Epsilon Constraint Method." In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-11496.

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Abstract The increase of heat generated in integrated circuit because of the miniaturization of electronic components requires more aggressive cooling solutions in order to minimize this high heat flux and address the temperature non-uniformity. In this paper, a manifold microchannel heat sinks has been investigated. In order to enhance the heat transfer performance of the microchannel, an improved version of the augmented epsilon constraint method is adopted for the optimization of the device. Four non-dimensional design variables have been used to describe the geometry of the manifold microchannel heat sinks. The thermal performance and the pumping power have been incorporated in the mathematical programming formulation as indicators of the thermal performance. A surrogate-based approximation based on the Response Surface Approximation has been utilized to evaluate these two objectives. This new mathematical approach has been implemented in the General Algebraic Modelling Systems (GAMS). Details about single and multi-objective optimization formulation of the problem will be disclosed. Optimal solutions describing the best geometrical configuration of the device will be computed. The implications of the geometrical configuration on the performance the manifold microchannel heat sinks will form part of the main contribution of this study.
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Xiong, Mengcheng, Haotong Fei, and Weixi Yan. "Research on Distribution Path of Multi-Target Urban UAV (unmanned aerial vehicle) based on epsilon-Constraint Method." In 2021 International Conference on Computer Information Science and Artificial Intelligence (CISAI). IEEE, 2021. http://dx.doi.org/10.1109/cisai54367.2021.00127.

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Yang, Zhixiang, Xinye Cai, and Zhun Fan. "Epsilon constrained method for constrained multiobjective optimization problems." In GECCO '14: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2014. http://dx.doi.org/10.1145/2598394.2610012.

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Lee, Yong Hoon, Jonathon Schuh, Randy H. Ewoldt, and James T. Allison. "Shape Parameterization Comparison for Full-Film Lubrication Texture Design." In ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/detc2016-60168.

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Minimizing energy loss and improving system load capacity and compactness are important objectives for fluid power applications. Recent studies have revealed that a micro-textured surface can reduce friction in full-film lubrication, and an asymmetric textured surface can further improve the performance by reducing friction and increasing normal force simultaneously. As an extension of these previous discoveries, we explore how enhanced texture design can maximize these objectives together. We design the surface texture using a set of distinct parameterizations, ranging from simple to complex (including very general geometries), to improve friction and normal force properties beyond what is possible for limited texture geometries. Here we use a rotational visco-rheometer configuration with a fixed bottom disc, a periodic textured surface, and a rotating top flat disc. The Reynolds equation is formulated in a cylindrical coordinate system and solved using a pseudo-spectral method to model Newtonian fluid flow within the gap between discs. Model assumptions include incompressibility, steady flow, constant viscosity, and a small gap height to texture radius ratio. Multiobjective optimization problems are solved using the epsilon-constraint method with an interior-point algorithm. The trade-off between competing objectives is quantified, revealing important insights. Arbitrary continuous texture geometries are represented using two dimensional cubic spline interpolation. Shifting to more general texture geometries resulted in significant simultaneous improvement in both performance metrics for full-film lubrication texture design. An important qualitative result is that textures resembling a helical blade tend to improve performance for rotating contacts in fluid power systems.
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Li, Yuzhe, Bo Li, Weiping Wang, and Nan Liu. "An Efficient Epsilon Selection Method for DP-ERM with Expected Accuracy Constraints." In 2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). IEEE, 2022. http://dx.doi.org/10.1109/trustcom56396.2022.00079.

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Han, Andi, and Junbin Gao. "Riemannian Stochastic Recursive Momentum Method for non-Convex Optimization." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/345.

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We propose a stochastic recursive momentum method for Riemannian non-convex optimization that achieves a nearly-optimal complexity to find epsilon-approximate solution with one sample. The new algorithm requires one-sample gradient evaluations per iteration and does not require restarting with a large batch gradient, which is commonly used to obtain a faster rate. Extensive experiment results demonstrate the superiority of the proposed algorithm. Extensions to nonsmooth and constrained optimization settings are also discussed.
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Dominguez-Isidro, Saul, Efren Mezura-Montes, and Cora B. Excelente-Toledo. "Variants of the Epsilon Constrained Method in a Memetic Differential Evolution: A Comparative Study." In 2019 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC). IEEE, 2019. http://dx.doi.org/10.1109/ropec48299.2019.9057134.

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