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1
Layeghy, Siamak, Farzaneh Pakzad, and Marius Portmann. "A New QoS Routing Northbound Interface for SDN." Australian Journal of Telecommunications and the Digital Economy 5, no. 1 (March 31, 2017): 92. http://dx.doi.org/10.18080/ajtde.v5n1.91.
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In this paper, we introduce SCOR (Software-defined Constrained Optimal Routing), a new Software Defined Networking (SDN) Northbound Interface for QoS routing and traffic engineering. SCOR is based on constraint-programming techniques and is implemented in the MiniZinc modelling language. It provides a powerful, high-level abstraction layer, consisting of 10 basic constraint-programming predicates. A key feature of SCOR is that it is declarative, where only the constraints and utility function of the routing problem need to be expressed, and the complexity of solving the problem is hidden from the user, and handled by a powerful generic solver. We show that the interface (set of predicates) of SCOR is sufficiently expressive to handle all the known and relevant QoS routing problems. We further demonstrate the practicality and scalability of the approach via a number of example scenarios, with varying network topologies, network sizes and number of flows.
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Layeghy, Siamak, Farzaneh Pakzad, and Marius Portmann. "A New QoS Routing Northbound Interface for SDN." Journal of Telecommunications and the Digital Economy 5, no. 1 (March 31, 2017): 92–115. http://dx.doi.org/10.18080/jtde.v5n1.91.
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In this paper, we introduce SCOR (Software-defined Constrained Optimal Routing), a new Software Defined Networking (SDN) Northbound Interface for QoS routing and traffic engineering. SCOR is based on constraint-programming techniques and is implemented in the MiniZinc modelling language. It provides a powerful, high-level abstraction layer, consisting of 10 basic constraint-programming predicates. A key feature of SCOR is that it is declarative, where only the constraints and utility function of the routing problem need to be expressed, and the complexity of solving the problem is hidden from the user, and handled by a powerful generic solver. We show that the interface (set of predicates) of SCOR is sufficiently expressive to handle all the known and relevant QoS routing problems. We further demonstrate the practicality and scalability of the approach via a number of example scenarios, with varying network topologies, network sizes and number of flows.
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Wei, Junbao, Haiyan Li, Ming Guo, Jing Li, and Huang Huang. "Backstepping Control Based on Constrained Command Filter for Hypersonic Flight Vehicles with AOA and Actuator Constraints." International Journal of Aerospace Engineering 2021 (September 2, 2021): 1–16. http://dx.doi.org/10.1155/2021/8620873.
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An antisaturation backstepping control scheme based on constrained command filter for hypersonic flight vehicle (HFV) is proposed with the consideration of angle of attack (AOA) constraint and actuator constraints of amplitude and rate. Firstly, the HFV system model is divided into velocity subsystem and height subsystem. Secondly, to handle AOA constraint, a constrained command filter is constructed to limit the amplitude of the AOA command and retain its differentiability. And the constraint range is set in advance via a prescribed performance method to guarantee that the tracking error of the AOA meets the constraint conditions and transient and steady performance. Thirdly, the proposed constrained command filter is combined with the auxiliary system for actuator constraints, which ensures that the control input meets the limited requirements of amplitude and rate, and the system is stable. In addition, the tracking errors of the system are proved to be ultimately uniformly bounded based on the Lyapunov stability theory. Finally, the effectiveness of the proposed method is verified by simulation.
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Sekizawa, Maisa, and Nobuyuki Kutsukake. "Maternal protectiveness is negatively associated with infant handling in wild Japanese macaques." Behaviour 156, no. 2 (2019): 155–79. http://dx.doi.org/10.1163/1568539x-00003534.
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Abstract Infant handling by a non-mother is common in many primate species. Despite the requirement of a triadic relationship among handler, mother, and infant, previous studies of infant handling have focused on characteristics of handler or interactions between mother and handler. In this study, we examined the influence of the mother–infant relationship (i.e., maternal style) on the frequency with which wild Japanese macaque (Macaca fuscata) infants were handled. We analysed behavioural data collected during 3 consecutive years and found that maternal style was characterised by three principal components: infant activity, rejection, and non-protectiveness. Infants who were less active and whose mothers were less protective received more frequent handling. These effects were particularly evident when handlers were thought to have less access to the infant. These complex interactions within the triadic relationship suggest that maternal style constrains the occurrence of infant handling in group-living primates.
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Hauser, Kris. "Semi-infinite programming for trajectory optimization with non-convex obstacles." International Journal of Robotics Research 40, no. 10-11 (January 10, 2021): 1106–22. http://dx.doi.org/10.1177/0278364920983353.
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This article presents a novel optimization method that handles collision constraints with complex, non-convex 3D geometries. The optimization problem is cast as a semi-infinite program in which each collision constraint is implicitly treated as an infinite number of numeric constraints. The approach progressively generates some of these constraints for inclusion in a finite nonlinear program. Constraint generation uses an oracle to detect points of deepest penetration, and this oracle is implemented efficiently via signed distance field (SDF) versus point cloud collision detection. This approach is applied to pose optimization and trajectory optimization for both free-flying rigid bodies and articulated robots. Experiments demonstrate performance improvements compared with optimizers that handle only convex polyhedra, and demonstrate efficient collision avoidance between non-convex CAD models and point clouds in a variety of pose and trajectory optimization settings.
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Rutter, Nicholas J., Tiffani J. Howell, Arthur A. Stukas, Jack H. Pascoe, and Pauleen C. Bennett. "Diving in Nose First: The Influence of Unfamiliar Search Scale and Environmental Context on the Search Performance of Volunteer Conservation Detection Dog–Handler Teams." Animals 11, no. 4 (April 20, 2021): 1177. http://dx.doi.org/10.3390/ani11041177.
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Conservation detection dogs (CDDs) are trained to locate biological material from plants and animals of interest to conservation efforts and are often more effective and economical than other detection methods. However, the financial costs of developing and appropriately caring for CDDs can nonetheless prohibit their use, particularly by smaller conservation organizations. Training skilled volunteers to work with suitable pet dogs may help address this constraint. We sought to further develop the skills of 13 volunteer dog–handler teams that were trained in a previous study to detect myrrh essential oil in controlled laboratory conditions. We assessed search sensitivity, search effort, search precision and false-alert instances through progressive training stages increasing in size and environmental complexity. First, teams searched various-sized areas before and after 12 weeks of search training on a sports-field. Next, teams searched various-sized areas before and after seven weeks of training in bushland. Overall, search sensitivity decreased by approximately 20% in each unfamiliar context, compared to performance in familiar contexts. However, sensitivity typically improved from baseline performance by 10–20% after a period of training. Six teams found at least 78% of targets after training in bushland, yet sensitivity ranged from 29% to 86% between teams. We maintain that the foundational skills developed previously were necessary to prepare volunteer teams for field surveys involving conservation related targets. However, our results highlight the need to also train volunteer CDD teams in search scale and environmental contexts similar to their intended working conditions.
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Gorti, Sreenivasa Rao, Salal Humair, Ram D. Sriram, Sarosh Talukdar, and Sesh Murthy. "Solving constraint satisfaction problems using ATeams." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 10, no. 1 (January 1996): 1–19. http://dx.doi.org/10.1017/s0890060400001256.
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AbstractThis paper presents an approach to solving constraint satisfaction problems using Asynchronous Teams of autonomous agents (ATeams). The focus for the constraint satisfaction problem is derived from an effort to support spatial layout generation in a conceptual design framework. The constraint specification allows a high-level representation and manipulation of qualitative geometric information. We present a computational technique based on ATeams to instantiate solutions to the constraint satisfaction problem. The technique uses a search for a solution in numerical space. This permits us to handle both qualitative relationships and numerical constraints in a unified framework. We show that simple knowledge, about human spatial reasoning and about the nature of arithmetic operators can be hierarchically encapsulated and exploited efficiently in the search. An example illustrates the generality of the approach for conceptual design. We also present empirical studies that contrast the efficiency of ATeams with a search based on genetic algorithms. Based on these preliminary results, we argue that the ATeams approach elegantly handles arbitrary sets of constraints, is computationally efficient, and hence merits further investigation.
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Yang, B. "Eigenvalue Inclusion Principles for Distributed Gyroscopic Systems." Journal of Applied Mechanics 59, no. 3 (September 1, 1992): 650–56. http://dx.doi.org/10.1115/1.2893773.
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In his famous treatise The Theory of Sound, Rayleigh enunciated an eigenvalue inclusion principle for the discrete, self-adjoint vibrating system under a constraint. According to this principle, the natural frequencies of the discrete system without and with the constraint are alternately located along the positive real axis. Although it is commonly believed that the same rule also applied for distributed vibrating systems, no proof has been given for the distributed gyroscopic system. This paper presents several eigenvalue inclusion principles for a class of distributed gyroscopic systems under pointwise constraints. A transfer function formulation is proposed to describe the constrained system. Five types of nondissipative constraints and their effects on the system natural frequencies are studied. It is shown that the transfer function formulation is a systematic and convenient way to handle constraint problems for the distributed gyroscopic system.
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Zhao, Tian Yang, Guo Bing Qiu, Ying Zhi Li, Wen Xia Liu, and Jian Hua Zhang. "Constrained Multi-Objective Differential Evolution for Security Constrained Economic/Environmental Dispatch." Applied Mechanics and Materials 291-294 (February 2013): 817–22. http://dx.doi.org/10.4028/www.scientific.net/amm.291-294.817.
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A newly constrained multi-objective differential evolution optimization technique (CMODE) for security constrained economic/environmental dispatch (EED) was proposed. The proposed CMODE evolved a constrained multi-objective version of differential evolution (DE) by employing the traditional multi-objective differential evolution (DEMO) and constrain handle technique to balance the search between feasible region and infeasible region. The proposed CMODE method had been applied to solve the security constrained EED problem. Experiments had been carried on a standard test system. The results demonstrate the high efficiency of the proposed method to solve security constrained EED problem, and the necessary of taking security constrains into consideration.
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Nordin, Axel, Damien Motte, Andreas Hopf, Robert Bjärnemo, and Claus-Christian Eckhardt. "Constraint-handling techniques for generative product design systems in the mass customization context." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 27, no. 4 (October 18, 2013): 387–99. http://dx.doi.org/10.1017/s0890060413000383.
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AbstractGenerative product design systems used in the context of mass customization are required to generate diverse solutions quickly and reliably without necessitating modification or tuning during use. When such systems are employed to allow for the mass customization of product form, they must be able to handle mass production and engineering constraints that can be time-consuming to evaluate and difficult to fulfill. These issues are related to how the constraints are handled in the generative design system. This article evaluates two promising sequential constraint-handling techniques and the often used weighted sum technique with regard to convergence time, convergence rate, and diversity of the design solutions. The application used for this purpose was a design system aimed at generating a table with an advanced form: a Voronoi diagram based structure. The design problem was constrained in terms of production as well as stability, requiring a time-consuming finite element evaluation. Regarding convergence time and rate, one of the sequential constraint-handling techniques performed significantly better than the weighted sum technique. Nevertheless, the weighted sum technique presented respectable results and therefore remains a relevant technique. Regarding diversity, none of the techniques could generate diverse solutions in a single search run. In contrast, the solutions from different searches were always diverse. Solution diversity is thus gained at the cost of more runs, but no evaluation of the diversity of the solutions is needed. This result is important, because a diversity evaluation function would otherwise have to be developed for every new type of design. Efficient handling of complex constraints is an important step toward mass customization of nontrivial product forms.
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Huang, Y. Q., S. L. Nie, and H. Ji. "Identification of Contamination Control Strategy for Fluid Power System Using an Inexact Chance-Constrained Integer Program." Journal of Applied Mathematics 2014 (2014): 1–19. http://dx.doi.org/10.1155/2014/146413.
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An inexact chance-constrained integer programming (ICIP) method is developed for planning contamination control of fluid power system (FPS). The ICIP is derived by incorporating chance-constrained programming (CCP) within an interval mixed integer linear programming (IMILP) framework, such that uncertainties presented in terms of probability distributions and discrete intervals can be handled. It can also help examine the reliability of satisfying (or risk of violating) system constraints under uncertainty. The developed method is applied to a case of contamination control planning for one typical FPS. Interval solutions associated with risk levels of constraint violation are obtained. They can be used for generating decision alternatives and thus help designers identify desired strategies under various environmental, economic, and system reliability constraints. Generally, willingness to take a higher risk of constraint violation will guarantee a lower system cost; a strong desire to acquire a lower risk will run into a higher system cost. Thus, the method provides not only decision variable solutions presented as stable intervals but also the associated risk levels in violating the system constraints. It can therefore support an in-depth analysis of the tradeoff between system cost and system-failure risk.
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Rossi, Francesca, Kristen Brent Venable, and Toby Walsh. "Preferences in Constraint Satisfaction and Optimization." AI Magazine 29, no. 4 (December 28, 2008): 58. http://dx.doi.org/10.1609/aimag.v29i4.2202.
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We review constraint-based approaches to handle preferences. We start by defining the main notions of constraint programming, then give various concepts of soft constraints and show how they can be used to model quantitative preferences. We then consider how soft constraints can be adapted to handle other forms of preferences, such as bipolar, qualitative, and temporal preferences. Finally, we describe how AI techniques such as abstraction, explanation generation, machine learning, and preference elicitation, can be useful in modelling and solving soft constraints.
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Chocat, Rudy, Loïc Brevault, Mathieu Balesdent, and Sébastien Defoort. "Modified Covariance Matrix Adaptation – Evolution Strategy algorithm for constrained optimization under uncertainty, application to rocket design." International Journal for Simulation and Multidisciplinary Design Optimization 6 (2015): A1. http://dx.doi.org/10.1051/smdo/2015001.
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The design of complex systems often induces a constrained optimization problem under uncertainty. An adaptation of CMA-ES(λ, μ) optimization algorithm is proposed in order to efficiently handle the constraints in the presence of noise. The update mechanisms of the parametrized distribution used to generate the candidate solutions are modified. The constraint handling method allows to reduce the semi-principal axes of the probable research ellipsoid in the directions violating the constraints. The proposed approach is compared to existing approaches on three analytic optimization problems to highlight the efficiency and the robustness of the algorithm. The proposed method is used to design a two stage solid propulsion launch vehicle.
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Gosain, Anjana, and Kavita Sachdeva. "Materialized View Selection for Query Performance Enhancement Using Stochastic Ranking Based Cuckoo Search Algorithm." International Journal of Reliability, Quality and Safety Engineering 27, no. 03 (September 18, 2019): 2050008. http://dx.doi.org/10.1142/s0218539320500084.
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Materialized view selection (MVS) improves the query processing efficiency and performance for making decisions effectively in a data warehouse. This problem is NP-hard and constrained optimization problem which involves space and cost constraint. Various optimization algorithms have been proposed in literature for optimal selection of materialized views. Few works exist for handling the constraints in MVS. In this study, authors have proposed the Cuckoo Search Algorithm (CSA) for optimization and Stochastic Ranking (SR) for handling the constraints in solving the MVS problem. The motivation behind integrating CS with SR is that fewer parameters have to be fine tuned in CS algorithm than in genetic and Particle Swarm Optimization (PSO) algorithm and the ranking method of SR handles the constraints effectively. For proving the efficiency and performance of our proposed algorithm Stochastic Ranking based Cuckoo Search Algorithm for Materialized View Selection (SRCSAMVS), it has been compared with PSO, genetic algorithm and the constrained evolutionary optimization algorithm proposed by Yu et al. SRCSAMVS outperforms in terms of query processing cost and scalability of the problem.
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Murrieta-Mendoza, Alejandro, Hugo Ruiz, and Ruxandra Mihaela Botez. "Horizontal flight trajectory optimization considering RTA constraints." MATEC Web of Conferences 314 (2020): 02002. http://dx.doi.org/10.1051/matecconf/202031402002.
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The increasing of flights around the world has led to various problems for the aeronautical industry such as saturated air space and higher levels of fossil fuel consumption. The way in which en-route flights are handled should be improved in order to increase airways’ capacity. A solution is to make aircraft to arrive at specific waypoints at a time constraint called Required Time of Arrival (RTA). Fossil fuel brings as a consequence the release of polluting particles to the atmosphere such as carbon dioxide and nitrogen oxides. It is thus desirable to compute the most economical trajectory in terms of fuel burn while fulfilling the RTA constraint. This article proposes a horizontal reference trajectory optimization algorithm based on the Particle Swarm Optimization technique in order to reduce fuel burn while fulfilling the RTA constraint. Results showed that for a flight without RTA constraint, up to 4% of fuel can be saved comparing against the trajectory of reference. The algorithm was normally able to meet the RTA constrain. However, aggressive RTA constraints might reduce the optimization levels of fuel compared with flights without RTA constraint.
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Lakmazaheri, Sivand. "Constraint-based reasoning via Grobner Bases." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 11, no. 1 (January 1997): 5–15. http://dx.doi.org/10.1017/s0890060400001803.
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AbstractConstraint-based reasoning is a problem-solving approach based on deductive reasoning. In this approach, a problem is modeled in terms of hypotheses and conclusion constraints, and it is solved via constraint satisfaction. The ability to handle linear and nonlinear algebraic constraints is essential for successful application of constraint-based reasoning in engineering. Due to the scarcity of algebraic techniques for satisfying nonlinear constraints, little attention has been paid to the use of constraint-based reasoning for solving nonlinear problems. This paper examines the use of the Grobner Bases method for satisfying nonlinear constraints in the context of constraint-based reasoning. After a brief introduction to the Grobner Bases method and its role in constraint-based reasoning, two examples are presented. The first example illustrates the use of Grobner bases, in the context of constraint-based reasoning, for reasoning about the behavior of beams. The second example illustrates the geometry configuration of truss structures via constraint-based reasoning.
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Barhorst, A. A., and L. J. Everett. "Contact/Impact in Hybrid Parameter Multiple Body Mechanical Systems." Journal of Dynamic Systems, Measurement, and Control 117, no. 4 (December 1, 1995): 559–69. http://dx.doi.org/10.1115/1.2801115.
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The multiple motion regime (free/constrained) dynamics of hybrid parameter multiple body (HPMB) systems is addressed. Impact response has characteristically been analyzed using impulse-momentum techniques. Unfortunately, the classical methods for modeling complex HPMB systems are energy based and have proven ineffectual at modeling impact. The problems are exacerbated by the problematic nature of time varying constraint conditions. This paper outlines the reformulation of a recently developed HPMB system modeling methodology into an impulse-momentum formulation, which systematically handles the constraints and impact. The starting point for this reformulation is a variational calculus based methodology. The variational roots of the methodology allows rigorous equation formulation which includes the complete nonlinear hybrid differential equations and boundary conditions. Because the methodology presented in this paper is formulated in the constraint-free subspace of the configuration space, both holonomic and nonholonomic constraints are automatically satisfied. As a result, the constraint-addition/deletion algorithms are not needed. Generalized forces of constraint can be directly calculated via the methodology, so the condition for switching from one motion regime to another is readily determined. The resulting equations provides a means to determine after impact velocities (and velocity fields for distributed bodies) which provide the after collision initial conditions. Finally the paper demonstrates, via example, how to apply the methodology to contact/impact in robotic manipulators and structural systems.
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Yang, Xiaohui, Xiaolong Zhang, Shaoping Xu, Yihui Ding, Kun Zhu, and Xiaoping Liu. "An Approach to the Dynamics and Control of Uncertain Robot Manipulators." Algorithms 12, no. 3 (March 26, 2019): 66. http://dx.doi.org/10.3390/a12030066.
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In this paper, a novel constraint-following control for uncertain robot manipulators that is inspired by analytical dynamics is developed. The motion can be regarded as external constraints of the system. However, it is not easy to obtain explicit equations for dynamic modeling of constrained systems. For a multibody system subject to motion constraints, it is a common practice to introduce Lagrange multipliers, but using these to obtain explicit dynamical equations is a very difficult task. In order to obtain such equations more simply, motion constraints are handled here using the Udwadia-Kalaba equation(UKE). Then, considering real-life robot manipulators are usually uncertain(but bounded), by using continuous controllers compensate for the uncertainties. No linearizations/approximations of the robot manipulators systems are made throughout, and the tracking errors are bounds. A redundant manipulator of the SCARA type as the example to illustrates the methodology. Numerical results are demonstrates the simplicity and ease of implementation of the methodology.
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Li, Haijiang, Hongxiang Ren, Shaoyang Qiu, and Chang Wang. "Physics-Based Simulation of Ocean Scenes in Marine Simulator Visual System." Water 12, no. 1 (January 12, 2020): 215. http://dx.doi.org/10.3390/w12010215.
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The realistic simulation of ocean scenes is of great significance in many scientific fields. We propose an improved Smoothed Particle Hydrodynamics (SPH) framework to simulate the ocean scenes. The improved SPH combines nonlinear constant density constraints and divergence-free velocity field constraint. Density constraints adjust the particle distribution on position layer, so that the density is constrained to a constant state. The addition of the divergence-free velocity field constraint significantly accelerates the convergence of constant density constraint and further reduces the density change. The simulation results show that the improved SPH has high solution efficiency, large time steps, and strong stability. Then, we introduce a unified boundary handling model to simulate coupling scenes. The model samples the boundary geometry as particles by means of single layer nonuniform sampling. The contribution of the boundary particles is taken into account when the physical quantities of fluid particles are computed. The unified model can handle various types of complex geometry adaptively. When rendering the ocean, we propose an improved anisotropic screen space fluid method, which alleviates the discontinuity problem near the boundary and maintains the anisotropy of particles. The research provides a theoretical reference for the highly believable maritime scene simulation in marine simulators.
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HU, YIBO. "HYBRID-FITNESS FUNCTION EVOLUTIONARY ALGORITHM BASED ON SIMPLEX CROSSOVER AND PSO MUTATION FOR CONSTRAINED OPTIMIZATION PROBLEMS." International Journal of Pattern Recognition and Artificial Intelligence 23, no. 01 (February 2009): 115–27. http://dx.doi.org/10.1142/s0218001409007004.
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For constrained optimization problems, evolutionary algorithms often utilize a penalty function to deal with constraints, even if it is difficult to control the penalty parameters. To overcome this shortcoming, this paper presents a new penalty function which has no parameter and can effectively handle constraint first, after which a hybrid-fitness function integrating this penalty function into the objective function is designed. The new fitness function can properly evaluate not only feasible solution, but also infeasible one, and distinguish any feasible one from an infeasible one. Meanwhile, a new crossover operator based on simplex crossover operator and a new PSO mutation operator are also proposed, which can produce high quality offspring. Based on these, a new evolutionary algorithm for constrained optimization problems is proposed. The simulations are made on ten widely used benchmark problems, and the results indicate the proposed algorithm is effective.
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Wang, Chunxiao, Yuqiang Wu, and Zhongcai Zhang. "Tracking control for strict-feedback nonlinear systems with time-varying full state constraints." Transactions of the Institute of Measurement and Control 40, no. 14 (February 5, 2018): 3964–77. http://dx.doi.org/10.1177/0142331217737596.
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This paper focuses on the tracking control problem for strict-feedback nonlinear systems subject to asymmetric time-varying full state constraints. Time-varying asymmetric barrier Lyapunov functions are employed to ensure time-varying constraint satisfaction. By allowing the barriers to vary with the desired trajectory in time, the initial condition requirements are relaxed. High-order coupling terms caused by backstepping are cancelled through a novel variable substitution for the first time. Besides the normal case, where the full knowledge of the system is available, we also handle scenarios of parametric uncertainties. Asymptotic tracking is achieved without violation of any constraints, and all signals in the closed-loop system are ultimately bounded. State-constrained systems with input saturation and bounded disturbances are also considered; the tracking error converges to a bounded set around zero. The performance of the asymmetric-barrier-Lyapunov-function-based control is illustrated through a numerical example.
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Gosain, Anjana, and Kavita Sachdeva. "Handling Constraints Using Penalty Functions in Materialized View Selection." International Journal of Natural Computing Research 8, no. 2 (April 2019): 1–17. http://dx.doi.org/10.4018/ijncr.2019040101.
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Materialized view selection (MVS) plays a vital role for efficiently making decisions in a data warehouse. This problem is NP-hard and constrained optimization problem. The authors have handled both the space and maintenance cost constraint using penalty functions. Three penalty function methods i.e. static, dynamic and adaptive penalty functions have been used for handling constraints and Backtracking Search Optimization algorithm (BSA) has been used for optimizing the total query processing cost. Experiments were conducted comparing the static, dynamic and adaptive penalty functions on varying the space constraint. The adaptive penalty function method yields the best results in terms of minimum query processing cost and achieves the optimality, scalability and feasibility of the problem on varying the lattice dimensions and on increasing the number of user queries. The authors proposed work has been compared with other evolutionary algorithms i.e. PSO and genetic algorithm and yields better results in terms of minimum total query processing cost of the materialized views.
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Sohn, Dongkyu, Shingo Mabu, Kotaro Hirasawa, and Jinglu Hu. "Optimization Method RasID-GA for Numerical Constrained Optimization Problems." Journal of Advanced Computational Intelligence and Intelligent Informatics 11, no. 5 (June 20, 2007): 469–77. http://dx.doi.org/10.20965/jaciii.2007.p0469.
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This paper proposes Adaptive Random search with Intensification and Diversification combined with Genetic Algorithm (RasID-GA) for constrained optimization. In the previous work, we proposed RasID-GA which combines the best properties of RasID and Genetic Algorithm for unconstrained optimization problems. In general, it is very difficult to find an optimal solution for constrained optimization problems because their feasible solution space is very limited and they should consider the objective functions and constraint conditions. The conventional constrained optimization methods usually use penalty functions to solve given problems. But, it is generally recognized that the penalty function is hard to handle in terms of the balance between penalty functions and objective functions. In this paper, we propose a constrained optimization method using RasID-GA, which solves given problems without using penalty functions. The proposed method is tested and compared with Evolution Strategy with Stochastic Ranking using well-known 11 benchmark problems with constraints. From the Simulation results, RasID-GA can find an optimal solution or approximate solutions without using penalty functions.
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Abuwarda, Zinab, and Tarek Hegazy. "Multi-dimensional optimization model for schedule fast-tracking without over-stressing construction workers." Canadian Journal of Civil Engineering 46, no. 12 (December 2019): 1160–73. http://dx.doi.org/10.1139/cjce-2018-0544.
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Fast-tracking is an important process to speed the delivery of construction projects. To support optimum fast-tracking decisions, this paper introduces a generic schedule optimization framework that integrates four schedule acceleration dimensions: linear activity crashing; discrete activity modes of execution; alternative network paths; and flexible activity overlapping. Because excessive schedule compression can lead to space congestion and overstressed workers, the optimization formulation uses specific variables and constraints to prevent simultaneous use of overlapping and crashing at the same activity segment. To handle complex projects with a variety of milestones, resource limits, and constraints, the framework has been implemented using the constraint programming (CP) technique. Comparison with a literature case study and further experimentation demonstrated the flexibility and superior performance of the proposed model. The novelty of the model stems from its integrated multi-dimensional formulation, its CP engine, and its ability to provide alternative fast-track schedules to strictly constrained projects without overstressing the construction workers.
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Kulkarni, Anand J., and K. Tai. "A Probability Collectives Approach with a Feasibility-Based Rule for Constrained Optimization." Applied Computational Intelligence and Soft Computing 2011 (2011): 1–19. http://dx.doi.org/10.1155/2011/980216.
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This paper demonstrates an attempt to incorporate a simple and generic constraint handling technique to the Probability Collectives (PC) approach for solving constrained optimization problems. The approach of PC optimizes any complex system by decomposing it into smaller subsystems and further treats them in a distributed and decentralized way. These subsystems can be viewed as a Multi-Agent System with rational and self-interested agents optimizing their local goals. However, as there is no inherent constraint handling capability in the PC approach, a real challenge is to take into account constraints and at the same time make the agents work collectively avoiding the tragedy of commons to optimize the global/system objective. At the core of the PC optimization methodology are the concepts of Deterministic Annealing in Statistical Physics, Game Theory and Nash Equilibrium. Moreover, a rule-based procedure is incorporated to handle solutions based on the number of constraints violated and drive the convergence towards feasibility. Two specially developed cases of the Circle Packing Problem with known solutions are solved and the true optimum results are obtained at reasonable computational costs. The proposed algorithm is shown to be sufficiently robust, and strengths and weaknesses of the methodology are also discussed.
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Chen, Gonggui, Lilan Liu, Yanyan Guo, and Shanwai Huang. "Multi-objective enhanced PSO algorithm for optimizing power losses and voltage deviation in power systems." COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering 35, no. 1 (January 4, 2016): 350–72. http://dx.doi.org/10.1108/compel-02-2015-0030.
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Purpose – For one thing, despite the fact that it is popular to research the minimization of the power losses in power systems, the optimization of single objective seems insufficient to fully improve the performance of power systems. Multi-objective VAR Dispatch (MVARD) generally minimizes two objectives simultaneously: power losses and voltage deviation. The purpose of this paper is to propose Multi-Objective Enhanced PSO (MOEPSO) algorithm that achieves a good performance when applied to solve MVARD problem. Thus, the new algorithm is worthwhile to be known by the public. Design/methodology/approach – Motivated by differential evolution algorithm, cross-over operator is introduced to increase particle diversity and reinforce global searching capacity in conventional PSO. In addition to that, a constraint-handling approach considering Constrain-prior Pareto-Dominance (CPD) is presented to handle the inequality constraints on dependent variables. Constrain-prior Nondominated Sorting (CNS) and crowding distance methods are considered to maintain well-distributed Pareto optimal solutions. The method combining CPD approach, CNS technique, and cross-over operator is called the MOEPSO method. Findings – The IEEE 30 node and IEEE 57 node on power systems have been used to examine and test the presented method. The simulation results show the MOEPSO method can achieve lower power losses, smaller voltage deviation, and better-distributed Pareto optimal solutions comparing with the Multi-Objective PSO approach. Originality/value – The most original parts include: the presented MOEPSO algorithm, the CPD approach that is used to handle constraints on dependent variables, and the CNS method which is considered to maintain a well-distributed Pareto optimal solutions. The performance of the proposed algorithm successfully reflects the value of this paper.
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Lakmazaheri, Sivand, and William J. Rasdorf. "Constraint logic programming for the analysis and partial synthesis of truss structures." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 3, no. 3 (August 1989): 157–73. http://dx.doi.org/10.1017/s0890060400001207.
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A general constraint-based formulation for the analysis and partial synthesis of two-dimensional truss structures is presented. This formulation is general in that it handles statically determinate and statically indeterminate trusses with pin and roller supports, and concentrated joint loads. The formulation is constraint-based in that the physical behavior of truss components is declaratively represented using constraints.The analysis and partial synthesis of a truss structure manifest themselves in proving the satisfiability of the constraints associated with the structural components. An artificial intelligence approach called constraint logic programming is used for representing and satisfying constraints. A constraint logic programming language, called CLP(R), is used for implementing the formulation. The implemented program consists of sixteen rules. These rules are used for both the analysis and partial synthesis of truss structures. Several truss analysis and synthesis examples using the formulation are presented.
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Doerr, Benjamin, Carola Doerr, Aneta Neumann, Frank Neumann, and Andrew Sutton. "Optimization of Chance-Constrained Submodular Functions." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 02 (April 3, 2020): 1460–67. http://dx.doi.org/10.1609/aaai.v34i02.5504.
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Submodular optimization plays a key role in many real-world problems. In many real-world scenarios, it is also necessary to handle uncertainty, and potentially disruptive events that violate constraints in stochastic settings need to be avoided. In this paper, we investigate submodular optimization problems with chance constraints. We provide a first analysis on the approximation behavior of popular greedy algorithms for submodular problems with chance constraints. Our results show that these algorithms are highly effective when using surrogate functions that estimate constraint violations based on Chernoff bounds. Furthermore, we investigate the behavior of the algorithms on popular social network problems and show that high quality solutions can still be obtained even if there are strong restrictions imposed by the chance constraint.
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Negrut, Dan, and Jose L. Ortiz. "A Practical Approach for the Linearization of the Constrained Multibody Dynamics Equations." Journal of Computational and Nonlinear Dynamics 1, no. 3 (February 25, 2006): 230–39. http://dx.doi.org/10.1115/1.2198876.
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The paper presents an approach to linearize the set of index 3 nonlinear differential algebraic equations that govern the dynamics of constrained mechanical systems. The proposed method handles heterogeneous systems that might contain flexible bodies, friction, control elements (user-defined differential equations), and nonholonomic constraints. Analytically equivalent to a state-space formulation of the system dynamics in Lagrangian coordinates, the proposed method augments the governing equations and then computes a set of sensitivities that provide the linearization of interest. The attributes associated with the method are the ability to handle large heterogeneous systems, ability to linearize the system in terms of arbitrary user-defined coordinates, and straightforward implementation. The proposed approach has been released in the 2005 version of the MSC.ADAMS/Solver(C++) and compares favorably with a reference method previously available. The approach was also validated against MSC.NASTRAN and experimental results.
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Hadfi, Rafik, and Takayuki Ito. "Complex Multi-Issue Negotiation Using Utility Hyper-Graphs." Journal of Advanced Computational Intelligence and Intelligent Informatics 19, no. 4 (July 20, 2015): 514–22. http://dx.doi.org/10.20965/jaciii.2015.p0514.
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We propose to handle the complexity of utility spaces used in multi-issue negotiation by adopting a new representation that allows a modular decomposition of the issues and the constraints. This is based on the idea that a constraint-based utility space is nonlinear with respect to issues, but linear with respect to the constraints. This allows us to rigorously map the utility space into an issue-constraint hyper-graph. Exploring the utility space reduces then to a message passing mechanism along the hyper-edges of the hyper-graph by means of utility propagation. Optimal contracts are found efficiently using a variation of the Max-Sum algorithm. We evaluate the model experimentally using parameterized nonlinear utility spaces, showing that it can handle a large family of complex utility spaces by finding optimal contracts, outperforming previous sampling-based approaches. We also evaluate the model in a negotiation setting. We show that under high complexity, social welfare could be greater than the sum of the individual agents’ best utilities.
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Nouhi, B., S. Talatahari, H. Kheiri, and C. Cattani. "Chaotic Charged System Search with a Feasible-Based Method for Constraint Optimization Problems." Mathematical Problems in Engineering 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/391765.
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Recently developed chaotic charged system search was combined to feasible-based method to solve constraint engineering optimization problems. Using chaotic maps into the CSS increases the global search mobility for a better global optimization. In the present method, an improved feasible-based method is utilized to handle the constraints. Some constraint design examples are tested using the new chaotic-based methods, and the results are compared to recognize the most efficient and powerful algorithm.
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Gotlieb, Arnaud, Dusica Marijan, and Helge Spieker. "ITE: A Lightweight Implementation of Stratified Reasoning for Constructive Logical Operators." International Journal on Artificial Intelligence Tools 29, no. 03n04 (June 2020): 2060006. http://dx.doi.org/10.1142/s0218213020600064.
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Constraint Programming (CP) is a powerful declarative programming paradigm where inference and search are interleaved to find feasible and optimal solutions to various type of constraint systems. However, handling logical connectors with constructive information in CP is notoriously difficult. This paper presents If Then Else (ITE), a lightweight implementation of stratified constructive reasoning for logical connectives. Stratification is introduced to cope with the risk of combinatorial explosion of constructing information from nested and combined logical operators. ITE is an open-source library built on top of SICStus Prolog clpfd, which proposes various operators, including constructive disjunction and negation, constructive implication and conditional. These operators can be used to express global constraints and to benefit from constructive reasoning for more domain pruning during constraint filtering. Even though ITE is not competitive with specialized filtering algorithms available in some global constraints implementations, its expressiveness allows users to easily define well-tuned constraints with powerful deduction capabilities. Our extended experimental results show that ITE is more efficient than available generic approaches that handle logical constraint systems over finite domains.
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Lidström, P. "Instantaneous impulses in multibody dynamics." Mathematics and Mechanics of Solids 22, no. 4 (October 19, 2015): 581–635. http://dx.doi.org/10.1177/1081286515598825.
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This paper considers instantaneous impulses in multibody dynamics. Instantaneous impulses may act on the multibody from its exterior or they may appear in its interior as a consequence of two of its parts interacting by an impact imposed by a unilateral constraint. The theory is based on the Euler laws of instantaneous impulses, which may be seen as a complement to the Euler laws for regular motions. Based on these laws, and specific continuum properties of the quantities involved, local balance laws for momentum and moment of momentum, involving instantaneous impulses and introducing the Cauchy impulse tensor, are derived. Thermodynamical restrictions on the impulse tensor are formulated based on the dissipation inequality. By stating a principle of virtual work for instantaneous impulses, and demonstrating its equivalence to Euler’s laws, Lagrange’s equations are derived. Lagrange’s equations are convenient to use in the case of multibody dynamics containing rigid as well as flexible parts. A central theme of this paper is the discussion of the interaction between parts of the multibody and their relation to geometrical and kinematical constraints. This interaction is severely affected by the presence of friction, which is notoriously difficult to handle. In a preparation for this discussion we first consider the one-point impact between two rigid bodies. The importance of the so-called impact tensor for this problem is demonstrated. In order to be able to handle the impact laws of Poisson and Stonge, an impact process, governed by a system of ordinary differential equations, is defined. Within this model phenomena, such as slip stop, slip start and slip direction reversal, may be handled. For a multibody with an arbitrary number of parts and multiple impacts, the situation is much more complicated and certain simplifications have to be introduced. Equations of motion for a multibody, consisting of rigid parts and in the presence of ideal bilateral constraints and unilateral constraints involving friction, are formulated. Unique solutions are obtained, granted that the mass matrix of the multibody system is non-singular, the constraint matrices satisfy specific full rank conditions and that the friction is not too high.
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Liu, Kaiping, Hee Beng Kuan Tan, and Xu Chen. "Automated Insertion of Exception Handling for Key and Referential Constraints." Journal of Database Management 24, no. 1 (January 2013): 1–19. http://dx.doi.org/10.4018/jdm.2013010101.
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Key and referential constraints are two main integrity constraints in database applications. These constraints can be automatically enforced by the Database Management System with their exception—violation from these constraints—handled by programmers. This paper proposes an approach to relieve the burden of programmers from mechanical coding for handling exceptions of these constraints violation by using program transformation. We first propose an extended abstract syntax tree to include SQL query semantics. Based on it, each code pattern that requires exception handling together with the exception handling code to be inserted is represented as a transformation rule. We provide two alternatives to handle the exceptions: one is to handle the exceptions in conjunction with the built-in enforcement feature in Database Management System; the other is handling them without using the feature provided in Database Management System. Hence, two types of transformation rules are provided accordingly. A tool GEHPHP (Generation of Exception Handling for PHP Systems) has been developed to implement the proposed approach. Experiments have also been conducted to evaluate the applicable of the approach.
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WANG, XIN, and HOWARD J. HAMILTON. "CLUSTERING SPATIAL DATA IN THE PRESENCE OF OBSTACLES." International Journal on Artificial Intelligence Tools 14, no. 01n02 (February 2005): 177–98. http://dx.doi.org/10.1142/s0218213005002053.
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Dealing with constraints due to obstacles is an important topic in constraint-based spatial clustering. In this paper, we proposed the DBRS_O method to identify clusters in the presence of intersected obstacles. Without doing any preprocessing, DBRS_O processes the constraints during clustering. DBRS_O can also avoid unnecessary computations when obstacles do not affect the clustering result. As well, DBRS_O can find clusters with arbitrary shapes, varying densities, deal with significant non-spatial attributes and handle large datasets.
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LEVER, JONATHAN. "A LOCAL SEARCH/CONSTRAINT PROPAGATION HYBRID FOR A NETWORK ROUTING PROBLEM." International Journal on Artificial Intelligence Tools 14, no. 01n02 (February 2005): 43–60. http://dx.doi.org/10.1142/s0218213005001989.
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This paper presents a hybrid algorithm that combines local search and constraint programming techniques to solve a network routing problem. The problem considered is that of routing traffic demands from a set of requests over a network with limited capacity so as to minimise the cost of any unrouted demands. The hybridisation is twofold: pure local search is used to find a good cost bound for a subsequent branch-and-bound optimisation phase, with local search again applied at the nodes of the branch-and-bound search tree. Constraint propagation occurs in the search tree to reduce the domains of the decision variable, using a set of constraints that are independent of the action of local search at the nodes. In contrast to previous constraint programming/local search hybridisations, here local search is used to satisfy the hard problem constraints, while optimisation is handled in the framework of constraint programming. The resulting algorithm is incomplete, but is shown to compare favourably with a complete approach to this problem.
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Fonseca, Daniel Guerra Vale da, André Felipe O. de A. Dantas, Carlos Eduardo Trabuco Dórea, and André Laurindo Maitelli. "Explicit GPC Control Applied to an Approximated Linearized Crane System." Journal of Control Science and Engineering 2019 (February 3, 2019): 1–13. http://dx.doi.org/10.1155/2019/3612634.
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This paper proposes a MIMO Explicit Generalized Predictive Control (EGPC) for minimizing payload oscillation of a Gantry Crane System subject to input and output constraints. In order to control the crane system efficiently, the traditional GPC formulation, based on online Quadratic Programming (QP), is rewritten as a multiparametric quadratic programming problem (mp-QP). An explicit Piecewise Affine (PWA) control law is obtained and holds the same performance as online QP. To test effectiveness, the proposed method is compared with two GPC formulations: one that handle constraints (CGPC) and another that does not handle constraints (UGPC). Results show that both EGPC and CGPC have better performance, reducing the payload swing when compared to UGPC. Also both EGPC and CGPC are able to control the system without constraint violation. When comparing EGPC to CGPC, the first is able to calculate (during time step) the control action faster than the second. The simulations prove that the overall performance of EGPC is superior to the other used formulations.
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Bouquet, Fabrice, and Philippe Jégou. "Using OBDDs to handle dynamic constraints." Information Processing Letters 62, no. 3 (May 1997): 111–20. http://dx.doi.org/10.1016/s0020-0190(97)00058-6.
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LIU, GUOHUA, and JIA-HUAI YOU. "Relating weight constraint and aggregate programs: Semantics and representation." Theory and Practice of Logic Programming 13, no. 1 (June 30, 2011): 1–31. http://dx.doi.org/10.1017/s147106841100038x.
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AbstractWeight constraint and aggregate programs are among the most widely used logic programs with constraints. In this paper, we relate the semantics of these two classes of programs, namely, the stable model semantics for weight constraint programs and the answer set semantics based on conditional satisfaction for aggregate programs. Both classes of programs are instances of logic programs with constraints, and in particular, the answer set semantics for aggregate programs can be applied to weight constraint programs. We show that the two semantics are closely related. First, we show that for a broad class of weight constraint programs, called strongly satisfiable programs, the two semantics coincide. When they disagree, a stable model admitted by the stable model semantics may be circularly justified. We show that the gap between the two semantics can be closed by transforming a weight constraint program to a strongly satisfiable one so that no circular models may be generated under the current implementation of the stable model semantics. We further demonstrate the close relationship between the two semantics by formulating a transformation from weight constraint programs to logic programs with nested expressions, which preserves the answer set semantics. Our study on the semantics leads to an investigation of a methodological issue, namely, the possibility of compact representation of aggregate programs by weight constraint programs. We show that almost all standard aggregates can be encoded by weight constraints compactly. This makes it possible to compute the answer sets of aggregate programs using the answer set programming solvers for weight constraint programs. This approach is compared experimentally with the ones where aggregates are handled more explicitly, which show that the weight constraint encoding of aggregates enables a competitive approach to answer set computation for aggregate programs.
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Barber, F. "Reasoning on Interval and Point-based Disjunctive Metric Constraints in Temporal Contexts." Journal of Artificial Intelligence Research 12 (February 1, 2000): 35–86. http://dx.doi.org/10.1613/jair.693.
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We introduce a temporal model for reasoning on disjunctive metric constraints on intervals and time points in temporal contexts. This temporal model is composed of a labeled temporal algebra and its reasoning algorithms. The labeled temporal algebra defines labeled disjunctive metric point-based constraints, where each disjunct in each input disjunctive constraint is univocally associated to a label. Reasoning algorithms manage labeled constraints, associated label lists, and sets of mutually inconsistent disjuncts. These algorithms guarantee consistency and obtain a minimal network. Additionally, constraints can be organized in a hierarchy of alternative temporal contexts. Therefore, we can reason on context-dependent disjunctive metric constraints on intervals and points. Moreover, the model is able to represent non-binary constraints, such that logical dependencies on disjuncts in constraints can be handled. The computational cost of reasoning algorithms is exponential in accordance with the underlying problem complexity, although some improvements are proposed.
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Kundu, Soumita, Tripti Chakrabarti, and Dipak Kumar Jana. "Optimal Manufacturing-Remanufacturing Production Policy for a Closed-Loop Supply Chain under Fill Rate and Budget Constraint in Bifuzzy Environments." International Journal of Mathematics and Mathematical Sciences 2014 (2014): 1–14. http://dx.doi.org/10.1155/2014/690435.
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We study a closed-loop supply chain involving a manufacturing facility and a remanufacturing facility. The manufacturer satisfies stochastic market demand by remanufacturing the used product into “as-new” one and producing new products from raw material in the remanufacturing facility and the manufacturing facility, respectively. The remanufacturing cost depends on the quality of used product. The problem is maximizing the manufacturer’s expected profit by jointly determining the collected quantity of used product and the ordered quantity of raw material. Following that we analyze the model with a fill rate constraint and a budget constraint separately and then with both the constraints. Next, to handle the imprecise nature of some parameters of the model, we develop the model with both constraints in bifuzzy environment. Finally numerical examples are presented to illustrate the models. The sensitivity analysis is also conducted to generate managerial insight.
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Allmendinger, Richard, and Joshua Knowles. "On Handling Ephemeral Resource Constraints in Evolutionary Search." Evolutionary Computation 21, no. 3 (September 2013): 497–531. http://dx.doi.org/10.1162/evco_a_00097.
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We consider optimization problems where the set of solutions available for evaluation at any given time t during optimization is some subset of the feasible space. This model is appropriate to describe many closed-loop optimization settings (i.e., where physical processes or experiments are used to evaluate solutions) where, due to resource limitations, it may be impossible to evaluate particular solutions at particular times (despite the solutions being part of the feasible space). We call the constraints determining which solutions are non-evaluable ephemeral resource constraints (ERCs). In this paper, we investigate two specific types of ERC: one encodes periodic resource availabilities, the other models commitment constraints that make the evaluable part of the space a function of earlier evaluations conducted. In an experimental study, both types of constraint are seen to impact the performance of an evolutionary algorithm significantly. To deal with the effects of the ERCs, we propose and test five different constraint-handling policies (adapted from those used to handle standard constraints), using a number of different test functions including a fitness landscape from a real closed-loop problem. We show that knowing information about the type of resource constraint in advance may be sufficient to select an effective policy for dealing with it, even when advance knowledge of the fitness landscape is limited.
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Fahmy, H., and D. Blostein. "A Graph-Rewriting Paradigm for Discrete Relaxation." International Journal of Pattern Recognition and Artificial Intelligence 12, no. 06 (September 1998): 763–99. http://dx.doi.org/10.1142/s0218001498000439.
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In image analysis, recognition of the primitives plays an important role. Subsequent analysis is used to interpret the arrangement of primitives. This subsequent analysis must make allowance for errors or ambiguities in the recognition of primitives. In this paper, we assume that the primitive recognizer produces a set of possible interpretations for each primitive. To reduce this primitive-recognition ambiguity, we use contextual information in the image, and apply constraints from the image domain. This process is variously termed constraint satisfaction, labeling or discrete relaxation. Existing methods for discrete relaxation are limited in that they assume a priori knowledge of the neighborhood model: before relaxation begins, the system is told (or can determine) which sets of primitives are related by constraints. These methods do not apply to image domains in which complex analysis is necessary to determine which primitives are related by constraints. For example, in music notation, we must recognize which notes belong to one measure, before it is possible to apply the constraint that the number of beats in the measure should match the time signature. Such constraints can be handled by our graph-rewriting paradigm for discrete relaxation: here neighborhood-construction is interleaved with constraint-application. In applying this approach to the recognition of simple music notation, we use approximately 180 graph-rewriting rules to express notational constraints and semantic-interpretation rules for music notation. The graph rewriting rules express both binary and higher-order notational constraints. As image-interpretation proceeds, increasingly abstract levels of interpretation are assigned to (groups of) primitives. This allows application of higher-level constraints, which can be formulated only after partial interpretation of the image.
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Daalmans, Jacco. "Constraint Simplification for Data Editing of Numerical Variables." Journal of Official Statistics 34, no. 1 (March 1, 2018): 27–39. http://dx.doi.org/10.1515/jos-2018-0002.
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Abstract Data editing is the process of checking and correcting data. In practise, these processes are often automated. A large number of constraints needs to be handled in many applications. This article shows that data editing can benefit from automated constraint simplification techniques. Performance can be improved, which broadens the scope of applicability of automatic data editing. Flaws in edit rule formulation may be detected, which improves the quality of automatic edited data.
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Sebastian, Gijo, Ying Tan, Denny Oetomo, and Iven Mareels. "Input and Output Constraints in Iterative Learning Control Design for Robotic Manipulators." Unmanned Systems 06, no. 03 (July 2018): 197–208. http://dx.doi.org/10.1142/s2301385018400095.
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Motivated by the safety requirement of rehabilitation robotic systems for after stroke patients, this paper handles position or output constraints in robotic manipulators when the patients repeat the same task with the robot. In order to handle output constraints, if all state information is available, a state feedback controller can ensure that the output constraints are satisfied while iterative learning control (ILC) is used to learn the desired control input through iterations. By incorporating the feedback control using barrier Lyapunov function with feed-forward control (ILC) carefully, the convergence of the tracking error, the boundedness of the internal state, the boundedness of input signals can be guaranteed along with the satisfaction of the output constraints over iterations. The effectiveness of the proposed controller is demonstrated using simulations from the model of EMU, a rehabilitation robotic system.
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Wang, Naige, Guohua Cao, Lu Yan, and Lei Wang. "Modeling and Control for a Multi-Rope Parallel Suspension Lifting System under Spatial Distributed Tensions and Multiple Constraints." Symmetry 10, no. 9 (September 18, 2018): 412. http://dx.doi.org/10.3390/sym10090412.
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The modeling and control of the multi-rope parallel suspension lifting system (MPSLS) are investigated in the presence of different and spatial distributed tensions; unknown boundary disturbances; and multiple constraints, including time varying geometric constraint, input saturation, and output constraint. To describe the system dynamics more accurately, the MPSLS is modelled by a set of partial differential equations and ordinary differential equations (PDEs-ODEs) with multiple constraints, which is a nonhomogeneous and coupled PDEs-ODEs, and makes its control more difficult. Adaptive boundary control is a recommended method for position regulation and vibration degradation of the MPSLS, where adaptation laws and a boundary disturbance observer are formulated to handle system uncertainties. The system stability is rigorously proved by using Lyapunov’s direct method, and the position and vibration eventually diminish to a bounded neighborhood of origin. The original PDEs-ODEs are solved by finite difference method, and the multiple constraints problem is processed simultaneously. Finally, the performance of the proposed control is demonstrated by both the results of ADAMS simulation and numerical calculation.
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Liu, Yongshuai, Jiaxin Ding, and Xin Liu. "IPO: Interior-Point Policy Optimization under Constraints." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 4940–47. http://dx.doi.org/10.1609/aaai.v34i04.5932.
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In this paper, we study reinforcement learning (RL) algorithms to solve real-world decision problems with the objective of maximizing the long-term reward as well as satisfying cumulative constraints. We propose a novel first-order policy optimization method, Interior-point Policy Optimization (IPO), which augments the objective with logarithmic barrier functions, inspired by the interior-point method. Our proposed method is easy to implement with performance guarantees and can handle general types of cumulative multi-constraint settings. We conduct extensive evaluations to compare our approach with state-of-the-art baselines. Our algorithm outperforms the baseline algorithms, in terms of reward maximization and constraint satisfaction.
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Arman, Molavi, Novan Wijaya, and Hafiz Irsyad. "Analisis Kinerja Web Server Menggunakan Algoritma Round Robin dan Least Connection." Jurnal Sisfokom (Sistem Informasi dan Komputer) 6, no. 1 (March 30, 2017): 55. http://dx.doi.org/10.32736/sisfokom.v6i1.143.
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In the industrialized world many companies are using web as a form of promotion or online transactions such as e-commerce. It handles millions of hit visits on the web server. There are many things that can cause the failure hit. One of them is the number of requests or transactions to the web server that is not able to be handled or the slowness of the response, which is very dangerous and detrimental for the company. The single web server with extremely expensive brands is a way to face the constraints overload, but only certain companies are able to have it. The issues faced, how to use some of the PCs as a web server with a reasonable economic value, could be empowered by implementing network load balancing technology. Network load balancing is a technology solution that is used, and expected to be able to handle the simultaneous load of web server with small output failure. Web server performance measurement at the round robin algorithm and least connection include parameters against components such as throughput, request loss, response time and cpu utilization, from the result of the measurement, it will be seen which is the best algorithm to use.
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Hou, Jie, Jihong Zhu, Jie Wang, and Weihong Zhang. "Topology optimization of the multi-fasteners jointed structure considering fatigue constraints." International Journal for Simulation and Multidisciplinary Design Optimization 9 (2018): A4. http://dx.doi.org/10.1051/smdo/2018003.
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This paper is to present an important issue of fatigue failure in the design of multi-fasteners jointed structure. To avoid failure in the connection area, Sines criterion is utilized. Fatigue constraints are handled in the context of stress based topology optimization. To eliminate the high stresses caused by the finite element modeling, the control volume is defined to evaluate the stress states around the fasteners. The standard topology optimization is extended to minimize the structural compliance with fatigue failure constraints. To address singularity problems related to stress constraints, q-p relaxation is used. P-norm is used as the constraints aggregation scheme. Basing on the above, the design sensitivity of fatigue constraints is derived and calculated. The proposed method is verified by a numerical example of an assembled I-beam. The comparisons of the numerical results have shown the effect of the fatigue constraint.
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DE CAT, BROES, and MAURICE BRUYNOOGHE. "Detection and exploitation of functional dependencies for model generation." Theory and Practice of Logic Programming 13, no. 4-5 (July 2013): 471–85. http://dx.doi.org/10.1017/s147106841300029x.
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AbstractRecent work in Answer Set Programming has integrated ideas from Constraint Programming. This has led to a new field called ASP Modulo CSP (CASP), in which the ASP language is enriched with constraint atoms representing constraint satisfaction problems. These constraints have a more compact grounding and are handled by a new generation of search algorithms. However, the burden is on the modeler to exploit these new constructs in his declarative problem specifications. Here, we explore how to remove this burden by automatically generating constraint atoms. We do so in the context of FO(·)IDP, a knowledge representation language that extends first-order logic with, among others, inductive definitions, arithmetic and aggregates. We uncover functional dependencies in declarative problem specifications with a theorem prover and exploit them with a transformation that introduces functions. Experimental evaluation shows that we obtain more compact groundings and better search performance.