Relevant bibliographies by topics / Epsilon-Constraint

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

Academic literature on the topic 'Epsilon-Constraint'

Author: Grafiati
Published: 21 February 2024
Last updated: 31 July 2025

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Journal articles on the topic "Epsilon-Constraint"

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Bai, Qinbo, Amrit Singh Bedi, Mridul Agarwal, Alec Koppel, and Vaneet Aggarwal. "Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Primal-Dual Approach." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 4 (2022): 3682–89. http://dx.doi.org/10.1609/aaai.v36i4.20281.

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Reinforcement learning is widely used in applications where one needs to perform sequential decisions while interacting with the environment. The problem becomes more challenging when the decision requirement includes satisfying some safety constraints. The problem is mathematically formulated as constrained Markov decision process (CMDP). In the literature, various algorithms are available to solve CMDP problems in a model-free manner to achieve epsilon-optimal cumulative reward with epsilon feasible policies. An epsilon-feasible policy implies that it suffers from constraint violation. An im
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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
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Feng, Songtao, Michael Dorothy, and Jie Fu. "Learning Nash Equilibrium of Markov Potential Games with a Shared Constraint via Primal-Dual Optimization." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 16 (2025): 16577–85. https://doi.org/10.1609/aaai.v39i16.33821.

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The problem of constrained Markov game has recently attracted interests in the study of multi-agent reinforcement learning (MARL). The existing literature has focused on safe MARL problems where safety constraints are imposed for each agent individually. In this work, we consider Markov potential game (MPG) with a shared constraint, where the cost function with respect to the constraint depends on states and joint actions of all agents. We adopt a primal-dual framework to tackle the problem and establish the Slater condition to ensure the strong duality. Moreover, we propose our primal-dual le
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Stanovov, Vladimir, Shakhnaz Akhmedova, and Eugene Semenkin. "Combined fitness–violation epsilon constraint handling for differential evolution." Soft Computing 24, no. 10 (2020): 7063–79. http://dx.doi.org/10.1007/s00500-020-04835-6.

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Mahdi, parvizi Elham Shadkam and Niloofar jahani. "A HYBRID COA/ε-CONSTRAINT METHOD FOR SOLVING MULTI-OBJECTIVE PROBLEMS". International Journal on Foundations of Computer Science & Technology (IJFCST) 5, № 5 (2023): 14. https://doi.org/10.5281/zenodo.8143468.

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In this paper, a hybrid method for solving multi-objective problem has been provided. The proposed method is combining the ε-Constraint and the Cuckoo algorithm. First the multi objective problem transfers into a single-objective problem using ε-Constraint, then the Cuckoo optimization algorithm will optimize the problem in each task. At last the optimized Pareto frontier will be drawn. The advantage of this method is the high accuracy and the dispersion of its Pareto frontier. In order to testing the efficiency of the suggested method, a lot of test problems have been solved u
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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 (2020): 600–624. http://dx.doi.org/10.1002/int.22219.

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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 (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 soluti
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Bozoklar, Emine, and Ebru Yılmaz. "Designing Sustainable Flexible Manufacturing Cells with Multi-Objective Optimization Models." Applied Sciences 14, no. 1 (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 mo
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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 (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
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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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Dissertations / Theses on the topic "Epsilon-Constraint"

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Ebadi, Nasim. "Estimating Costs of Reducing Environmental Emissions From a Dairy Farm: Multi-objective epsilon-constraint Optimization Versus Single Objective Constrained Optimization." Thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/99304.

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Agricultural production is an important source of environmental emissions. While water quality concerns related to animal agriculture have been studied extensively, air quality issues have become an increasing concern. Due to the transfer of nutrients between air, water, and soil, emissions to air can harm water quality. We conduct a multi-objective optimization analysis for a representative dairy farm with two different approaches: nonlinear programming (NLP) and ϵ-constraint optimization to evaluate trade-offs among reduction of multiple pollutants including nitrogen (N), phosphorus (P), gre
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Tamby, Satya. "Approches génériques pour la résolution de problèmes d'optimisation discrète multiobjectif." Electronic Thesis or Diss., Paris Sciences et Lettres (ComUE), 2018. http://www.theses.fr/2018PSLED048.

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Lorsque les problèmes de décision font intervenir plusieurs critères contradictoires, la notion d'optimum n'a plus réellement de sens. Dès lors, les décideurs sont amenés à considérer tous les différents compromis possibles. Même s'il est possible d'éliminer ceux qui sont dominés, c'est à dire moins bons qu'un autre sur tous les critères, l'ensemble est d'autant plus complexe à déterminer que ses éléments peuvent être très nombreux. Nous nous intéressons ici aux problèmes d'optimisation combinatoire multicritères. Afin que notre méthode soit adaptable pour un grand nombre de problèmes, nous em
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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 perfor
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Gonzalez, rodriguez Magno angel. "Intégration de concepts de gestion de chaine logistique en boucle fermée (CLSCM) et d'analyse du cycle de vie (ACV) : contribution à l’économie circulaire et application aux batteries au plomb." Electronic Thesis or Diss., Toulouse, INPT, 2020. http://www.theses.fr/2020INPT0114.

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Durant les dix dernières années, le concept de chaîne d'approvisionnement a évolué vers une approche intégrée considérant simultanément les chaînes d'approvisionnement amont et aval. Cette évolution a donné naissance à la chaîne d'approvisionnement en boucle fermée (CLSC), visant à optimiser l'utilisation des matériaux issus de divers processus de fabrication. Malgré les avancées notables dans la gestion et la conception des CLSC, la plupart des approches de recherche ont surtout mis l'accent sur les aspects économiques, laissant souvent de côté ou traitant séparément les préoccupations enviro
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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 d
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Book chapters on the topic "Epsilon-Constraint"

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Reyes-Bustos, Cid. "Extended Divisibility Relations for Constraint Polynomials of the Asymmetric Quantum Rabi Model." In International Symposium on Mathematics, Quantum Theory, and Cryptography. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5191-8_13.

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Abstract The quantum Rabi model (QRM) is widely regarded as one of the fundamental models of quantum optics. One of its generalizations is the asymmetric quantum Rabi model (AQRM), obtained by introducing a symmetry-breaking term depending on a parameter $$\varepsilon \in \mathbb {R}$$ to the Hamiltonian of the QRM. The AQRM was shown to possess degeneracies in the spectrum for values $$\epsilon \in 1/2\mathbb {Z}$$ via the study of the divisibility of the so-called constraint polynomials. In this article, we aim to provide further insight into the structure of Juddian solutions of the AQRM by
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Azizi, Mahdi, and Siamak Talatahari. "Material Generation Algorithm Combined with Epsilon Constraint Handling Scheme for Engineering Optimization." In Handbook of Nature-Inspired Optimization Algorithms: The State of the Art. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-07516-2_9.

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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. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72654-6_10.

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Cai, Siye, Guoyu Chen, Xiaoxu Gu, Zhanpeng Liu, Yuhang Meng, and Shuai Fan. "Optimal Scheduling Approach for Virtual Capacity Augmentation of Muti-Distribution Transformer Area Based on Epsilon-Constraint Method." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2024. https://doi.org/10.1007/978-981-97-8816-3_28.

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Conference papers on the topic "Epsilon-Constraint"

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Ferenc Dömény, Martin, Melánia Puskás, Levente Kovács, and Dániel András Drexler. "Multi-Objective Chemotherapy Optimization Using NSGA-II and Epsilon-Constraint Method." In 2024 IEEE 22nd Jubilee International Symposium on Intelligent Systems and Informatics (SISY). IEEE, 2024. http://dx.doi.org/10.1109/sisy62279.2024.10737606.

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Becerra, Ricardo Landa, and Carlos A. Coello Coello. "Epsilon-constraint with an efficient cultured differential evolution." In the 2007 GECCO conference companion. ACM Press, 2007. http://dx.doi.org/10.1145/1274000.1274052.

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Crawford, Victoria G. "Faster Guarantees of Evolutionary Algorithms for Maximization of Monotone Submodular Functions." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/229.

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In this paper, the monotone submodular maximization problem (SM) is studied. SM is to find a subset of size kappa from a universe of size n that maximizes a monotone submodular objective function f . We show using a novel analysis that the Pareto optimization algorithm achieves a worst-case ratio of (1 − epsilon)(1 − 1/e) in expectation for every cardinality constraint kappa < P , where P ≤ n + 1 is an input, in O(nP ln(1/epsilon)) queries of f . In addition, a novel evolutionary algorithm called the biased Pareto optimization algorithm, is proposed that achieves a worst-case ratio of (1 −
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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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Boulif, Menouar, and Karim Atif. "An Exact Multiobjective Epsilon-Constraint Approach for the Manufacturing Cell Formation Problem." In 2006 International Conference on Service Systems and Service Management. IEEE, 2006. http://dx.doi.org/10.1109/icsssm.2006.320737.

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Tingting, Miao, and Qin Tianbao. "A bi-objective mixed capacitated arc routing problem based on epsilon constraint algorithm." In 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC2023), edited by Dimitrios A. Karras and Simon X. Yang. SPIE, 2023. http://dx.doi.org/10.1117/12.2684682.

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Zhu, Yanhui, Samik Basu, and A. Pavan. "Improved Evolutionary Algorithms for Submodular Maximization with Cost Constraints." In Thirty-Third International Joint Conference on Artificial Intelligence {IJCAI-24}. International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/ijcai.2024/783.

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We present an evolutionary algorithm evo-SMC for the problem of Submodular Maximization under Cost constraints (SMC). Our algorithm achieves 1/2-approximation with a high probability 1-1/n within O(n2 K) iterations, where K denotes the maximum size of a feasible solution set with cost constraint B. To the best of our knowledge, this is the best approximation guarantee offered by evolutionary algorithms for this problem. We further refine evo-SMC and develop st-evo-SMC. This stochastic version yields a significantly faster algorithm while maintaining the approximation ratio of 1/2, with probabi
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Javadi, Mohammad, Mohamed Lotfi, Gerardo J. Osorio, et al. "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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Fan, Zhun, Hui Li, Caimin Wei, et al. "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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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 microc
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