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: 1 June 2024

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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 (June 28, 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 important question here is whether we can achieve epsilon-optimal cumulative reward with zero constraint violations or not. To achieve that, we advocate the use of a randomized primal-dual approach to solve the CMDP problems and propose a conservative stochastic primal-dual algorithm (CSPDA) which is shown to exhibit O(1/epsilon^2) sample complexity to achieve epsilon-optimal cumulative reward with zero constraint violations. In the prior works, the best available sample complexity for the epsilon-optimal policy with zero constraint violation is O(1/epsilon^5). Hence, the proposed algorithm provides a significant improvement compared to the state of the art.
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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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Stanovov, Vladimir, Shakhnaz Akhmedova, and Eugene Semenkin. "Combined fitness–violation epsilon constraint handling for differential evolution." Soft Computing 24, no. 10 (March 10, 2020): 7063–79. http://dx.doi.org/10.1007/s00500-020-04835-6.

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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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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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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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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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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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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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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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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), greenhouse gas (GHG), and ammonia. We evaluated twenty-six different scenar- ios in which we define incremental reductions of N, P, ammonia, and GHG from five to 25% relative to a baseline scenario. The farm entails crop production, livestock production (dairy and broiler), and manure management activities. Results from NLP optimization indicate that reducing P and ammonia emissions is relatively more expen- sive than N and GHG. This result is also confirmed by the ϵ-constraint optimization. However, the latter approach provides limited evidence of trade-offs among reduction of farm pollutants and net returns, while the former approach includes different re- duction scenarios that make trade-offs more evident. Results from both approaches indicate changes in crop rotation and land retirement are the best strategies to reduce N and P emissions while cow diet changes involving less forage represents the best strategy to reduce ammonia and GHG emissions.
Master of Science
Human activities often damage and deplete the environment. For instance, nutrient pollution into air and water, which mostly comes from agricultural and industrial activ- ities, results in water quality degradation. Thus, mitigating the detrimental impacts of human activities is an important step toward environmental sustainability. Reducing environmental impacts of nutrient pollution from agriculture is a complicated problem, which needs a comprehensive understanding of types of pollution and their reduction strategies. Reduction strategies need to be both feasible and financially viable. Con- sequently, practices must be carefully selected to allow farmers to maximize their net return while reducing pollution levels to reach a satisfactory level. Thus, this paper conducts a study to evaluate the trade-offs associated with farm net return and re- ducing the most important pollutants generated by agricultural activities. The results of this study show that reducing N and GHG emissions from a representative dairy farm is less costly than reducing P and ammonia emissions, respectively. In addition, reducing one pollutant may result in reduction of other pollutants. In general, for N and P emissions reduction land retirement and varying crop rotations are the most effective strategies. However, for reducing ammonia and GHG emissions focusing on cow diet changes involving less forage is the most effective strategy.
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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 employons la programmation mathématique en nombres entiers pour définir l'ensemble des solutions réalisables
Real world problems often involve several conflicting objectives. Thus, solution of interests are efficient solutions which have the property that an improvement on one objective leads to a decay on another one. The image of such solutions are referred to as nondominated points. We consider here the standard problem of computing the set of nondominated points, and providing a corresponding efficient solution for each point
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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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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 environnementales via l'analyse du cycle de vie (ACV). La fermeture de la boucle de la chaîne d'approvisionnement conduit généralement à un système plus complexe que la chaîne d'approvisionnement traditionnelle. Ainsi, il est impératif de développer des méthodes quantitatives et des modèles spécifiques pour aider les gestionnaires et professionnels à créer des systèmes en boucle fermée plus efficaces, rentables et durables. L'objectif scientifique majeur de ce travail consiste à développer une analyse intégrée des concepts de gestion des CLSC et d’analyse du cycle de vie en explorant l'effet miroir qui existe entre ces deux domaines. Le cas d’étude des batteries au plomb dans les véhicules automobiles, en particulier pour les véhicules électriques, vient appuyer ces travaux. La formulation du modèle est établie sur une procédure de programmation mathématique linéaire en variables mixtes (MILP) avec une approche multicritère liée à la minimisation des coûts et à l'impact environnemental, considérant cinq échelons (fournisseurs, producteurs, distributeurs, grossistes et détaillants) dans le réseau amont et sept échelons (centres de collecte et de recyclage, élimination des produits, démontage, élimination des matières premières, tiers et recyclage) dans le réseau aval. La stratégie multi-niveaux et multi-périodes consiste d'abord à identifier et réduire les critères significatifs qui peuvent être utilisés dans la procédure d'optimisation multi-objectifs (dans ce cas, bi-objectifs). Deux critères majeurs ont émergé : le coût total de la chaîne d'approvisionnement et les émissions totales de gaz à effet de serre, reconnus comme étant contradictoires, justifiant ainsi la mise en œuvre d'une procédure d'epsilon-contrainte. La première application d'une méthode d'aide à la décision (M-TOPSIS et TOPSIS) a permis d'identifier les configurations candidates de la chaîne d'approvisionnement. Une analyse du cycle de vie a ensuite été réalisée sur l'ensemble des solutions du front de Pareto afin de mener une analyse multicritère sur tous les critères de la méthode d'analyse d'impact sélectionnée (Impact 2002+) et le critère de coût. Cette étape a révélé des solutions plus intéressantes concernant ce groupe de critères que celles identifiées au niveau précédent, validant ainsi la démarche. Du point de vue stratégique, cela a nécessité le développement de sous-modules environnementaux pour les blocs de la chaîne d'approvisionnement afin de calculer systématiquement les indicateurs environnementaux à partir de l'extraction de la base de données EcoInvent et des facteurs d'impact de la méthode d'analyse utilisée dans l'étude. Enfin, une étude de sensibilité a montré que pour l'étude de cas, (i) une augmentation du pourcentage d'utilisation des matières premières récupérées d'un produit à recycler, (ii) une augmentation du taux de récupération, (iii) une amélioration du processus de fabrication/refabrication vis-à-vis des émissions de GES sont des paramètres particulièrement significatifs pour améliorer de la performance de tous les indicateurs
Over the past decade, the supply chain concept has undergone significant evolution, transitioning toward an integrated approach that considers both upstream and downstream chains simultaneously. This evolution has led to the development of the closed-loop supply chain (CLSC), aimed at optimizing material utilization across various manufacturing processes. While progress in managing and designing CLSCs has been notable, most research approaches have primarily focused on economic aspects, often addressing environmental concerns as an afterthought or separately via life cycle assessment (LCA). The closure of the supply chain loop typically results in a more intricate system compared to traditional supply chains. Consequently, there is an urgent need for specifically tailored quantitative methods and models to assist managers and professionals in creating more efficient, cost-effective, and sustainable closed-loop systems. The overarching scientific objective of this study is to conduct an integrated analysis that combines CLSC management concepts and Life Cycle Assessment, exploring their interdependence. This investigation will be supported by the increased utilization of lead-acid batteries in motor vehicles, especially in the context of electric vehicles, considered a promising future vehicle option.The model formulation relies on a mixed-variable linear mathematical programming procedure (MILP), incorporating a multi-criteria approach focused on cost minimization and environmental impact. This formulation considers five tiers in the forward network (suppliers, producers, distributors, wholesalers, and retailers) and seven tiers in the reverse network (collection and recycling centers, product disposal, disassembly plant, raw material disposal, third parties, and remanufacturing). The multi-level multi-period strategy involves initially identifying and reducing significant criteria applicable in the multi-objective (in this case, bi-objective) optimization procedure. Two crucial criteria emerged: the total cost of the supply chain and total greenhouse gas emissions, which were recognized as conflicting, warranting the implementation of an epsilon-constraint procedure.The first application of decision support methods (M-TOPSIS and TOPSIS) facilitated the identification of potential supply chain configurations. Subsequently, a life cycle assessment was conducted on the Pareto front-end solutions, enabling a comprehensive multi-criteria analysis involving the selected impact analysis method (Impact 2002+) and the cost criterion. This step revealed solutions that outperformed those previously identified, validating the approach.Strategically, this required the development of environmental submodules for the supply chain blocks to consistently compute environmental indicators. This involved extracting data from the EcoInvent database and utilizing impact factors pertinent to the study's analysis method.Lastly, a sensitivity study highlighted that, for the case study: (i) an increase in the percentage of raw materials recovered from a product designated for recycling, (ii) an improved recovery rate, and (iii) enhancements in the manufacturing/remanufacturing process regarding GHG emissions, are particularly significant in improving the performance of all indicators
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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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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, 149–68. Singapore: 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 extending the divisibility properties and the relations between the constraint polynomials with the solution of the AQRM in the Bargmann space. In particular we discuss a conjecture proposed by Masato Wakayama.
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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, 165–87. Cham: 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, 96–104. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72654-6_10.

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Conference papers on the topic "Epsilon-Constraint"

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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. New York, New York, USA: 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}. California: 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 − epsilon)(1 − 1/e − epsilon) in expectation for every cardinality constraint kappa < P in O(n ln(P ) ln(1/epsilon)) queries of f . Further, the biased Pareto optimization algorithm can be modified in order to achieve a a worst-case ratio of (1 − epsilon)(1 − 1/e − epsilon) in expectation for cardinality constraint kappa in O(n ln(1/epsilon)) queries of f . An empirical evaluation corroborates our theoretical analysis of the algorithms, as the algorithms exceed the stochastic greedy solution value at roughly when one would expect based upon our analysis.
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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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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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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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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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Narawade, Vaibhav Eknath, and Uttam D. Kolekar. "EACSRO: Epsilon constraint-based Adaptive Cuckoo Search algorithm for rate optimized congestion avoidance and control in wireless sensor networks." In 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC). IEEE, 2017. http://dx.doi.org/10.1109/i-smac.2017.8058272.

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