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检索条件"主题词=mixed integer linear programming"

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Multiobjective Optimization Model for Regime Adjustment in Crude Oil Production

Multiobjective Optimization Model for Regime Adjustment in C...

引用

Conferencia Latinoamericana En Informatica (CLEI)

作者： Matías Micheletto Javier Marenco Rómulo Alcoleas Carlos De Marziani Rodrigo Santos IIDEPyS GSJ CONICET-UNPSJB Comodoro Rivadavia Universidad Torcuato Di Tell Buenos Aires UNPSJB Comodoro Rivadavia DIEC UNS ICIC CONICET-UNS Bahía Blanca

ISBN: (数字)9798331540975

ISBN: (纸本)9798331540982

production battery in the oil industry is a set of equipment and facilities used in the initial stages of crude oil processing at an oilfield. At various stages of operation, it may be necessary to restrict or increase its processing capacity, meaning that the gross volume to be received must be adjusted. In remote areas where connectivity and infrastructure may be limited, it is necessary for an operator to approach the well in person to make manual adjustments directly to the pumping system. Proper planning of the well route for adjusting regimes directly impacts the operating costs of the oilfield. In this work in progress, a mixed integer linear programming model for this problem is proposed, by considering the production, operation, and modification restrictions of the pumping regime of each well. Preliminary results are presented, which show that the model can be used in practice.

关键词： Costs Oils Computational modeling Optimization models Production Planning mixed integer linear programming Batteries Petroleum industry

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Partial Context-Sensitive Pointer Integrity for Real-time Embedded Systems

Partial Context-Sensitive Pointer Integrity for Real-time Em...

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Real-Time Systems Symposium (RTSS)

作者： Yujie Wang Cailani Lemieux-Mack Thidapat Chantem Sanjoy Baruah Ning Zhang Bryan C. Ward Washington University in St. Louis Vanderbilt University Virginia Tech

ISBN: (数字)9798331540265

ISBN: (纸本)9798331540272

Safety- and mission-critical cyber-physical systems (CPSs) require temporal correctness to ensure safe physical behavior. This manifests as strict timing requirements, which cannot be missed at runtime. Counter-intuitively, this implies that real-time tasks can be delayed so long as they remain guaranteed to meet their deadlines. This paper explores how extra time in a schedule can be analytically recapitalized for the purpose of applying stronger security protection within individual tasks at compile time. This is achieved through the development of a partial context-sensitive pointer-integrity framework (ParCSPI). In this framework, more fine-grained policies can be enforced, with greater runtime overheads, where so doing does not violate real-time constraints. A whole-system optimization framework based upon a mixed-integer linear programming approach to fixed-priority response-time analysis is used to identify precisely which contexts can be checked within the available system-wide time while maximizing system-wide security. ParCSPI leverages Arm pointer authentication (PA) to encode context-based equivalence classes into the modifiers of the pointer signature and is implemented using a customized program analyzer and LLVM compiler passes. An evaluation of ParCSPI is presented that includes per-task and system-wide overhead and security tradeoffs, as well as a demonstration on a real-world CPS. Empirical results are presented showing that ParCSPI achieves up to 62% pointer-integrity protection with only 10% worst-case execution time (WCET) overhead, and can find optimal security trade-offs in complex real-time task sets as well as approximate them in reasonable time.

关键词： Schedules Runtime Program processors Prototypes Real-time systems Timing mixed integer linear programming Security Protection Optimization

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Constraint-Aware Resource Management for Cyber-Physical Systems

Constraint-Aware Resource Management for Cyber-Physical Syst...

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Design, Automation and Test in Europe Conference and Exhibition

作者： Justin McGowen Ismet Dagli Neil T. Dantam Mehmet E. Belviranli Computer Science Department Colorado School of Mines

ISBN: (数字)9783981926385

ISBN: (纸本)9798350348606

Cyber-physical systems (CPS) such as robots and self-driving cars pose strict physical requirements to avoid failure. Scheduling choices impact these requirements. This presents a challenge: how do we find efficient schedules for CPS with heterogeneous processing units, such that the schedules are resource-bounded to meet the physical requirements? We propose the creation of a structured system, the Constrained Autonomous Workload Scheduler, which determines scheduling decisions with direct relations to the environment. By using a representation language (AuWL), Timed Petri nets, and mixed-integer linear programming, our scheme offers novel capabilities to represent and schedule many types of CPS workloads, real world constraints, and optimization criteria.

关键词： Schedules Processor scheduling Petri nets Cyber-physical systems mixed integer linear programming Autonomous automobiles Resource management

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Multiobjective Branch-and-Cut Method with Shared Cutting Plane Information: A Case Study on Optimizing Garbage Collection

Multiobjective Branch-and-Cut Method with Shared Cutting Pla...

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International Symposium on Soft Computing and Intelligent Systems (SCIS)

作者： Tomoki Kaho Kazutoshi Sakakibara Mikiharu Arimura Shinya Watanabe The Graduate School of Engineering Muroran Institute of Technology Muroran Japan Department of Data Science Faculty of Information Engineering Toyama Prefectural University Toyama Japan Department of Engineering Muroran Institute of Technology Muroran Japan Department of Sciences and Informatics Muroran Institute of Technology Muroran Japan

ISBN: (数字)9798350373332

ISBN: (纸本)9798350373349

This paper presents an application of the Multi-Objective Branch-and-Bound based on Decomposition (MOBB/D) method for Branch-and-Cut, combining branch-and-bound and cutting-plane methods. Traditionally, multi-objective branch-and-bound methods for multi-objective mixed-integer linear programming problems struggle with the large number of Pareto-optimal solutions. MOBB/D addresses this by decomposing multi-objective problems into single-objective subproblems using weight vectors and applying branch-and-bound to each, with information sharing between nearby subproblems. In this paper, we customize the MOBB/D method for Branch-and-Cut to achieve an efficient search by sharing cutting plane information in MOBB/D. We demonstrate our approach with a case study on garbage collection planning in Muroran City, Hokkaido, Japan. This case study combines facility location and route optimization within a multi-objective framework, balancing the burdens on residents and garbage collection workers. Numerical experiments compare execution times and solutions with and without cutting plane sharing, and visualize the impact of different objective balance preferences on route optimization. The results show substantial efficiency gains and provide practical insights for multi-objective optimization in urban planning.

关键词： Visualization Scalability Roads Urban planning Vectors Real-time systems Planning mixed integer linear programming Computational efficiency Optimization

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Exploring Non-linear programming Formulations in QuantumCircuitOpt for Optimal Circuit Design

Exploring Non-Linear Programming Formulations in QuantumCirc...

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Quantum Computing Software (QCS), IEEE/ACM International Workshop on

作者： Elena R. Henderson Harsha Nagarajan Carleton Coffrin Information Systems and Modeling Los Alamos National Laboratory Los Alamos NM USA Applied Math. and Plasma Physics (T-5) Los Alamos National Laboratory Los Alamos NM USA Advanced Network Science Initiative Los Alamos National Laboratory Los Alamos NM USA

ISBN: (纸本)9781665475372

Given the limitations of current hardware, the theoretical gains promised by quantum computing remain unre-alized across practical applications. But the gap between theory and hardware is closing, assisted by developments in quantum algorithmic modeling. One such recent development is Quan-tumCircuitOpt (QCOpt), an open-source software framework that leverages state-of-the-art optimization-based solvers to find provably optimal compact circuit decompositions, which are exact up to global phase and machine precision. The quantum circuit design problem can be modeled using non-linear, non-convex constraints. However, QCOpt reformulates these non-linear constraints using well-known linearization techniques such that the resulting design problem is solved as a mixed-integer linear programming model. In this work, we instead explore whether the QCOpt's model could also be effective with a continuous Non-linear programming (NLP) model obtained via relaxation of the integer variables in the non-linear constraints. We are able to present not only multiple significant enhancements to QCOpt, with up to 11.3x speed up in run times on an average, but also opportunities for more generally exploring the behavior of gradient-based NLP solvers.

关键词： Conferences Software algorithms Quantum mechanics linearization techniques programming Hardware mixed integer linear programming

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Flexibility Provision by Smart Homes in Integrated Energy Management Systems

Flexibility Provision by Smart Homes in Integrated Energy Ma...

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International Conference on Environment and Electrical Engineering (EEEIC)

作者： Mohammad Sadegh Javadi Ali Esmaeel Nezhad Pedro H.J. Nardelli Subham Sahoo Institute for Systems and Computer Engineering Technology and Science (INESC TEC) Porto Portugal Department of Electrical Engineering School of Energy Systems LUT University Lappeenranta Finland Department of Energy Technology Aalborg University Aalborg Denmark

ISBN: (数字)9781665485371

ISBN: (纸本)9781665485388

This paper presents a mathematical problem formulation for energy management systems for smart homes. The flexibility can be provided by a home energy management system (HEMS) in a local energy community. The main concept is to model the flexibility provision and flexibility procurement within the energy community that can be provided to the aggregator from active consumers. The integrated energy management model is coded as a standard mixed-integer linear programming (MILP) model which can be solved by open-source tools like the PuLP package developed in Python. The simulation results confirm the performance of the proposed model in terms of flexibility provided by the centralized integrated energy system introduced in this paper.

关键词： Home appliances Costs Simulation Smart homes Mathematical models mixed integer linear programming Energy management systems

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Design for shape control of tensegrities

Design for shape control of tensegrities

引用

American Control Conference (ACC)

作者： B. de Jager Department of Mechanical Engineering Technische Universiteit Eindhoven Eindhoven Netherlands

This paper proposes and demonstrates procedures to optimally design tensegrity structures actuation, based on closed loop shape control requirements, while at the same time a feasible path for realizing a desired shape is synthesized. The procedures are employing different optimization based formulations of a set of requirements needed for shape control. The specific procedure demonstrated is based on a mixed integer linear programming formulation, one of the simplest possible. It is possible to formulate the design problem more generally, but then the computations become more involved, inhibiting a real time implementation of the procedure. The demonstration is for a simple planar tensegrity, but the procedures can be applied to more general structures without modification

关键词： Shape control Tendons Bars Actuators mixed integer linear programming Art Biological cells Biological system modeling Force control Mechanical engineering

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Enhanced Power System Restoration Through MILP Black Start Allocation Optimization

Enhanced Power System Restoration Through MILP Black Start A...

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IEEE Kansas Power and Energy Conference

作者： Shaharier Kabir Abu Shufian Riadul Islam Nasif Hannan Md. Saniat Rahman Zishan Shaikh Anowarul Fattah Dept. of EEE American International University-Bangladesh Dhaka Bangladesh Dept. of ECE Lamar University Texas USA Dept. of EEE Bangladesh University of Engineering and Technology Dhaka Bangladesh

ISBN: (数字)9798350372403

ISBN: (纸本)9798350372410

Restoring a power system following a blackout is a critical undertaking, necessitating the efficient allocation of Black Start (BS) resources—generators capable of initiating without external power. This research introduces an innovative approach to address a critical challenge in power system restoration—optimal black start allocation. Efficient allocation of resources when power systems face blackouts is crucial for rapid restoration. Leveraging the power of mixed integer linear programming (MILP), this study formulates and solves the black start allocation problem with the primary objective of minimizing allocation costs, all while satisfying many operational constraints. These constraints include ensuring power supply meets demand, adhering to generator output limits and ramping rates, and enforcing time-bound generator startup decisions. Furthermore, it maintains power flow equilibrium and network stability through branch flow and voltage magnitude constraints. This research offers a promising solution to enhance the resilience and reliability of power systems by optimizing the allocation of black start resources. This would reduce downtime ultimately and mitigate the far-reaching impacts of blackouts on society and the economy.

关键词： Voltage Optimal scheduling Power system stability Generators Power system restoration Power system reliability mixed integer linear programming

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Design Diversity for Mitigating Monoculture Induced Threats

Design Diversity for Mitigating Monoculture Induced Threats

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IEEE International Symposim on High Assurance Systems Engineering

作者： Qi Cheng Kevin Kwiat Charles A. Kamhoua School of Electrical and Computer Engineering Oklahoma State University Stillwater OK Information Directorate Air Force Research Laboratory Rome NY

Monoculture induced threats such as "pass the hash" attacks can spread more easily through a system of similar components. Introducing a few different and more robust components in the system has the potential to mitigate such situations. In this paper, we propose a constrained resource allocation optimization framework exploring the binary decision diagram (BDD) and mixed integer linear programming techniques. An illustrative example is provided.

关键词： Security Boolean functions Computers Binary decision diagrams Optimization mixed integer linear programming

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Spinning reserve estimation in microgrids

Spinning reserve estimation in microgrids

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IEEE/PES Transmission and Distribution Conference and Exhibition: Asia and Pacific

作者： M. Q. Wang H. B. Gooi School of Electrical & Electronic Engineering Nanyang Technological University Singapore

ISBN: (纸本)9781424452293

In this paper, a probabilistic methodology for estimating the spinning reserve in microgrids is proposed. The spinning reserve amount is determined by maximizing the total profit while considering the unreliability of units and uncertainties caused by nondispatchable units and load. In order to reduce the computation burden, various uncertainties are aggregated and rounding to an equivalent distribution. The optimization is solved by mixed integer linear programming.

关键词： Spinning Wind speed Uncertainty Strontium Power system modeling mixed integer linear programming Load forecasting Weibull distribution Energy management Load modeling

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