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检索条件"主题词=Constraint Programming"

共 1863 条记录，以下是841-850 订阅

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Optimal Planning and Operation Scheduling of Battery Storage Units in Distribution Systems

Optimal Planning and Operation Scheduling of Battery Storage...

引用

IEEE Milan PowerTech Conference

作者： Mirtaheri, Hamidreza Bortoletto, Alessandro Fantino, Maurizio Mazza, Andrea Marzband, Mousa LINKS Fdn Turin Italy Politecn Torino Dept Energy Turin Italy Northumbria Univ Dept Phys & Elect Engn Newcastle Upon Tyne Tyne & Wear England

ISBN: (纸本)9781538647226

In the last years, the electricity system has been subject to a paradigm change, due to increasing share of installed renewable energy sources-based power plants. This fact is leading electrical system - which proper operation was however affected by the intermittent nature of renewables - to become more "green". The union of energy chain de-carbonization with service reliability opens new opportunities for storage systems, although their relatively high cost highlighted the importance of optimal decisions in sizing, placing and operation of such systems. For addressing these aspects, appropriate mathematical models and optimization methods are needed: in this paper, a novel and efficient hybrid optimization algorithm is introduced, to solve i) sizing, ii) placement and iii) operation of arbitrary storage systems. This method is then applied to a low voltage grid, to demonstrate the effectiveness of the proposed methodology.

关键词： smart grid storage system optimization genetic algorithm constraint programming siting sizing scheduling

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Towards model-based Generation and Optimization of AUTOSAR Runnable-to-Task Mapping 22

Towards model-based Generation and Optimization of AUTOSAR R...

引用

ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C)

作者： Wilhelm, Thomas Weber, Raphael Vector Informat GmbH D-93053 Regensburg Germany

ISBN: (纸本)9781728151250

In this paper we present work towards automating two process steps supporting the optimization of the runnable-to-task mapping in automotive multi-core control units. We describe these steps in close relation to the AUTOSAR methodology to facilitate the integration with existing design processes. The first step is the automated generation of an initial configuration that balances the core utilization using constraint programming. The second step is the optimization of an existing configuration based on dynamic system behavior using an evolutionary algorithm. An abstract intermediate representation provides interoperability with existing AUTOSAR tools. We use a small case study to evaluate the feasibility of our approach.

关键词： AUTOSAR runnable-to-task mapping constraint programming model-based development optimization

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Type-Directed Program Synthesis and constraint Generation for Library Portability 28

Type-Directed Program Synthesis and Constraint Generation fo...

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28th International Conference on Parallel Architectures and Compilation Techniques (PACT)

作者： Collie, Bruce Ginsbach, Philip O'Boyle, Michael F. P. Univ Edinburgh Sch Informat Edinburgh Midlothian Scotland

ISBN: (纸本)9781728136134

Fast numerical libraries have been a cornerstone of scientific computing for decades, but this comes at a price. Programs may be tied to vendor specific software ecosystems resulting in polluted, non-portable code. As we enter an era of heterogeneous computing, there is an explosion in the number of accelerator libraries required to harness specialized hardware. We need a system that allows developers to exploit ever-changing accelerator libraries, without over-specializing their code. As we cannot know the behavior of future libraries ahead of time, this paper develops a scheme that assists developers in matching their code to new libraries, without requiring the source code for these libraries. Furthermore, it can recover equivalent code from programs that use existing libraries and automatically port them to new interfaces. It first uses program synthesis to determine the meaning of a library, then maps the synthesized description into generalized constraints which are used to search the program for replacement opportunities to present to the developer. We applied this approach to existing large applications from the scientific computing and deep learning domains. Using our approach, we show speedups ranging from 1.1x to over 10x on end to end performance when using accelerator libraries.

关键词： program synthesis code rejuvenation constraint programming compilers

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Towards a Parallel constraint Solver for Cloud Computing Environments 5

Towards a Parallel Constraint Solver for Cloud Computing Env...

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5th IEEE International Conference on Big Data Computing Service and Applications (IEEE BigDataService) / Workshop on Big Data in Water Resources, Environment, and Hydraulic Engineering / Workshop on Medical, Healthcare, Using Big Data Technologies

作者： Menouer, Tarek Sukhija, Nitin Darmon, Patrice UMANIS Levallois Perret France Slippery Rock Univ Penn Dept Comp Sci Slippery Rock PA USA

ISBN: (纸本)9781728100593

This paper presents a parallel constraint programming (CP) solver for Optimizing the Performance of CP problems in Cloud Computing Environments. The parallelization of constraint programming (CP) solvers is widely proposed in the literature to improve the resolution of CP problems by reducing the computing time. Moreover, the current CP problems addressed by the industry involve big data scenarios and solving such complex problems in less time require the use of scalable many-core computing resources that are easily offered by the cloud computing environments. However, achieving optimal performance on CP solvers is a major concern while dealing with cloud infrastructure. To address this issue, we propose a parallelization approach that enables communication between several parallel CP solvers to efficiently exploit the massively available computing resources, thus minimizing the performance degradation of the CP solvers in cloud environments. The benefit of employing our approach is insuring good load balancing between all computing cores that encompasses the cloud infrastructure.

关键词： Parallelization constraint programming Load Balancing Grid Computing Cloud Computing

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Constrained optimization under uncertainty for decision-making problems: Application to Real-Time Strategy games

Constrained optimization under uncertainty for decision-maki...

引用

IEEE Congress on Evolutionary Computation (IEEE CEC)

作者： Antuori, Valentin Richoux, Florian Univ Nantes LS2N Nantes France Natl Inst Informat JFLI CNRS Tokyo Japan

ISBN: (纸本)9781728121536

Decision-making problems can be modeled as combinatorial optimization problems with constraint programming formalisms such as Constrained Optimization Problems. However, few constraint programming formalisms can deal with both optimization and uncertainty at the same time, and none of them are convenient to model problems we tackle in this paper. Here, we propose a way to deal with combinatorial optimization problems under uncertainty within the classical Constrained Optimization Problems formalism by injecting the Rank Dependent Utility from decision theory. We also propose a proof of concept of our method to show it is implementable and can solve concrete decision-making problems using a regular constraint solver, and propose a bot that won the partially observable track of the 2018 mu RTS AI competition. Our result shows it is possible to handle uncertainty with regular constraint programming solvers, without having to define a new formalism neither to develop dedicated solvers. This brings new perspective to tackle uncertainty in constraint programming.

关键词： Combinatorial optimization Uncertainty Decision-making problems constraint programming Decision theory Real-Time Strategy games

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An Integrated Two-Stage Optimization Method for Job-Shop Bottleneck Planning and Scheduling

An Integrated Two-Stage Optimization Method for Job-Shop Bot...

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IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)

作者： Gao, Na Moon, Seung Ki Nanyang Technol Univ Sch Mech & Aerosp Engn Singapore Singapore

ISBN: (纸本)9781728138046

In many literatures, planning and scheduling problems have been considered separately. Furthermore, resource constraints for scheduling are not only relevant for equipment, but are also strongly affected by second resources and set up conversions. This paper derives how constraint programming enables problem-dependent specialization and increases planning and scheduling efficiency. constraint programing based scheduling involves multi-resources capacity limit, demand fulfill, precedence, initialization, down activities and sequence-dependent set up. Then, we improve this model to address on more complex problems by introducing a two-stage optimization method to decrease the computational burden. Finally, computational results are demonstrated to show the efficiency of the proposed method for a real time large scale planning and scheduling problem.

关键词： Bottleneck Optimization Capacity Allocation constraint programming Mixed Integer programming Multi-Resources

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constraint-Programmed Initial Sizing of Analog Operational Amplifiers 37

Constraint-Programmed Initial Sizing of Analog Operational A...

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37th IEEE International Conference on Computer Design (ICCD)

作者： Abel, Inga Neuner, Maximilian Graeb, Helmut Tech Univ Munich Chair Elect Design Automat D-80333 Munich Germany

ISBN: (纸本)9781538666487

This paper presents a new method to automate the initial sizing of operational amplifiers. The method emulates the manual design procedure. The sizing task is formulated as a constraint programming problem. Two new algorithms are introduced: First, a hierarchical structural analysis of functional blocks that automatically sets up the analytical equations for the sizing. And second, a heuristic to guide branching process of a constraint programming solver. We achieve a reproduction of the manual proceeding of designers and at the same time an automation of the set-up of the design problem, reducing the set-up effort from months to seconds. 16 topologies, including different variants of two-stage, folded-cascode, telescopic and symmetrical op-amps, are considered at this time. In this paper, experimental results for a two-stage op-amp and a folded-cascode op-amp are presented to show the effectiveness of the approach.

关键词： Analog circuit sizing Automatic initial sizing Automatic sizing CMOS constraint programming Operational amplifiers

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G2Q: Haskell constraint Solving 12

G2Q: Haskell Constraint Solving

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12th ACM SIGPLAN International Symposium on Haskell (Haskell)

作者： Hallahan, William T. Xue, Anton Piskac, Ruzica Yale Univ Comp Sci New Haven CT 06520 USA

ISBN: (纸本)9781450368131

constraint solvers give programmers a useful interface to solve challenging constraints at runtime. In particular, SMT solvers have been used for a vast variety of different, useful applications, ranging from strengthening Haskell's type system to verifying network protocols. Unfortunately, interacting with constraint solvers directly from Haskell requires a great deal of manual effort. Data must be represented in and translated between two forms: that understood by Haskell, and that understood by the SMT solver. Such a translation is often done via printing and parsing text, meaning that any notion of type safety is lost. Furthermore, direct translations are rarely sufficient, as it typically takes many iterations on a design in order to get optimal - or even acceptable - performance from a SMT solver on large scale problems. This need for iteration complicates the translation issue: it is easy to introduce a runtime bug and frustrating to fix said bug. To address these problems, we introduce a new constraint solving library, G2Q. G2Q includes a quasiquoter that allows solving constraints written in Haskell itself, thus unifying data representation, ensuring correct typing, and simplifying development iteration. We describe the API to our library and its backend. Rather than a direct translation to SMT formulas, G2Q makes use of the G2 symbolic execution engine. This allows G2Q to solve problems that are out of scope when directly encoded as SMT formulas. Finally, we demonstrate the usability of G2Q via four example programs.

关键词： constraint solving Haskell constraint programming symbolic execution

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Parallel Stochastic Portfolio Search for constraint Solving 17

Parallel Stochastic Portfolio Search for Constraint Solving

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IEEE Int Conf on Parallel and Distributed Processing with Applications, Big Data and Cloud Computing, Sustainable Computing and Communications, Social Computing and Networking (ISPA/BDCloud/SocialCom/SustainCom)

作者： Liu, Ke Loeffler, Sven Hofstedt, Petra Brandenburg Univ Technol Cottbus Senftenberg Dept Math & Comp Sci MINT Cottbus Germany

ISBN: (纸本)9781728143286

It is not uncommon to observe that the performance of constraint solving on a particular problem can be easily influenced by altering the search strategy, restart policy and their parameter settings, etc. In the multicore era, this lack of robustness can be exploited to speed up the constraint solving by designing a parallel portfolio search which simultaneously executes different incarnations of a sequential solver on the same problem. In this paper, we first investigate the techniques of existing single-solver-based portfolio approach in detail. On this basis, we gained insight into how to improve the portfolio approach. We then present the parallel stochastic portfolio search that benefits from the explicit early diversity resulted from randomization and parallelism. Performance evaluation on some classical constraint satisfaction problems benchmarks shows that our technique can solve harder instances compared to the existing portfolio;and not only that, it has advantages of simplicity for implementation and good scalability.

关键词： constraint programming constraint satisifaction problem Parallel constraint solving Portfolio search

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A Study In Three Practical Management Science Problems

A Study In Three Practical Management Science Problems

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作者： John S. F. Lyons University of Western Ontario

学位级别：博士

This study of practical problems in Management Science (MS) describes novel mathematical models for three different decision settings. It addresses questions of: (a) what optimal route should be taken through a time-windows and topographically complex network; (b) what optimal sequencing of scheduled surgeries best coordinates flow of patients through central recovery; and (c) what prices should be charged and what stock amounts should be produced for two markets or channels to maximize profit explicitly, given various capacity and uncertainty conditions. The first problem is in a sport analytics context, using a novel Integer programming and big data from Whistler-Blackcomb ski resort. The second is to coordinate dozens of surgeries at London Health Sciences Centre, using a novel constraint programming model mapped to and parameterized with hospital data, including a tool for visualizing process and patient flow. The third problem is relevant to almost any business with a secondary market or sales channel, as it helps them identify profit optimal prices based on simple demand estimates and cost information they can easily provide for their own setting. The studies use fundamentally different operational research techniques, in each case uniquely extended to the problem setting. The first two are combinatorial problems, neither one extremely beyond human cognitive ability, and both involving lots of uncertainty, and thus the sort of problem managers tend to dismiss as not efficient or practical to solve analytically. We show in the first study that vastly more skiers could achieve the challenge by following our route recommendation, unintuitive as are some of its elements, initially. In the second study, our scheduling model consistently outperforms currently unstructured-independent approach at the hospital. The final study is mathematical but demonstrates that by considering distinct market costs in pricing a firm can invariably earn more profit.

关键词： route optimization sports analytics operating room scheduling integer programming dual channel pricing constraint programming

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