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

共 3301 条记录，以下是141-150 订阅

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mixed integer linear programming Model for Workload Leveling on Offshore Platform of Petroleum Company

Mixed Integer Linear Programming Model for Workload Leveling...

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2010 International Conference on Intelligent Computation Technology and Automation(2010 智能计算技术与自动化国际会议 ICICTA 2010)

作者： Malinee Wongruean Chidchanok Lursinsap Siripun Sanguansintukul Krung Sinapiromsaran Advanced Virtual and Intelligent Computing (AVIC) Center Department of Mathematics Faculty of Science Chulalongkom University Bangkok Thailand

ISBN: (纸本)9781424472796

The problem of automatic workload leveling and balancing occurring in the maintenance and inspection section of Petroleum Company in Thailand is studied, in each year, the company receives a tremendous number of maintenance and inspection work orders regarding the gas and oil offshore platforms. Each worker is capable of doing more than one work order. Workload leveling is needed in order to distribute all works for limited number of personnel and accommodations on offshore platform. mixed integer linear programming (MILP) technique using branch and cut method is utilized for this problem.

关键词： Workload leveling assignment optimization Branch and Cut mixed integer linear programming resource availability constraint offshore platform of petroleum company

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mixed integer linear programming model for integrating cell formation, group layout and group scheduling

Mixed integer linear programming model for integrating cell ...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Sherif A. Fahmy Department of Industrial Engineering Cairo University Giza Egypt

Cellular manufacturing systems (CMS) are production systems that typically comprise a number of manufacturing cells served by a centralized material handling system. Designing such systems includes three major decisions; cell formation (CF), group layout (GL), and group scheduling (GS). Traditionally, these three decisions have been dealt with separately, which has usually lead to less than optimal system performance. In this paper, a new mixed integer linear programming (MILP) model is proposed for the integrated CF, GL and GS problem, to efficiently design and operate CMSs. The model solves the integrated problem, taking into consideration intercellular and intracellular transportation times to determine the optimal cell formation, layout of machines and schedule of parts on the machines, simultaneously. Sequence-dependent set up times are also considered in the model. The performance of the model is tested by solving problems previously introduced in the literature considering two objectives; minimizing the makespan or minimizing the mean flow time in the system. The results show that the proposed model is efficient in solving small to medium-sized problems.

关键词： Mathematical model Layout Transportation Job shop scheduling Manufacturing mixed integer linear programming

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Optimal Trajectory Planning for Trains Using mixed integer linear programming

Optimal Trajectory Planning for Trains Using Mixed Integer L...

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14th International IEEE Conference on Intelligent Transportation Systems (ITSC)

作者： Wang, Yihui De Schutter, Bart Ning, Bin Groot, Noortje van den Boom, Ton J. J. Beijing Jiaotong Univ State Key Lab Traff Control & Safety Beijing Peoples R China Delft Univ Technol Delft Ctr Syst & Control NL-2600 AA Delft Netherlands

ISBN: (纸本)9781457721977

The optimal trajectory planning for trains under constraints and fixed maximal arrival time is considered. The variable line resistance (including variable grade profile, tunnels, and curves) and arbitrary speed restrictions are included in this approach. The objective function is a trade-off between the energy consumption and the riding comfort. First, the nonlinear train model is approximated by a piece-wise affine model. Next, the optimal control problem is formulated as a mixed integer linear programming (MILP) problem, which can be solved efficiently by existing solvers. The good performance of this approach is demonstrated via a case study.

关键词： Approximation methods Energy consumption Force Mathematical model Optimal control Resistance Trajectory affine transforms energy consumption energy consumption integer programming linear programming mixed integer linear programming nonlinear train model o

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Optimal Microgrid Component Sizing using mixed integer linear programming

Optimal Microgrid Component Sizing using Mixed Integer Linea...

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IEEE Transportation Electrification Conference and Expo (ITEC)

作者： Yu, Xiang Eric Malysz, Pawel Sirouspour, Shahin Emadi, Ali McMaster Univ Hamilton ON L8S 4L8 Canada

ISBN: (纸本)9781479956159

This paper proposes a novel method for determining the optimal number of renewable energy and storage components in a microgrid given typical load profiles, local pricing regime, and capital costs. Case studies using solar panels and advanced lead acid battery modules are performed under residential, commercial, and off-grid sites. Simple mixed integer linear programming (MILP) optimization problems are formulated, presented, and solved in each scenario where economic analysis highlights the utility of the proposed approach.

关键词： Batteries Economics Electricity Microgrids Optimization Pricing mixed integer linear programming MICRO-GRID Pricing Batteries Electricity economics component sizing Solar collectors

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Optimizing the Hyperparameters of a mixed integer linear programming Solver to Speed up Electric Vehicle Charging Control 1

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23rd European International Conference on the Applications of Evolutionary Computation (EvoApplications) Held as Part of EvoStar Conference

作者： Ishihara, Takahiro Limmer, Steffen Tokyo Inst Technol Grad Sch Engn Dept Syst & Control Tokyo 1528552 Japan Honda Res Inst Europe GmbH D-63073 Offenbach Germany

ISBN: (数字)9783030437220

ISBN: (纸本)9783030437213;9783030437220

Optimization of charging profiles for controlled charging of electric vehicles is commonly done via mixed integer linear programming. The runtime of the optimization can represent an issue for the practical use. However, by tuning the parameter setting of the employed solver, it is possible to speed up the optimization process. The present work evaluates two popular hyperparameter tuning tools - irace (iterated racing) and SMAC (sequential model-based algorithm configuration) - for the optimization of parameters of the SCIP (Solving Constraint integer Programs) solver with the objective to speed up the solving process for four common variants of the electric vehicle charging scheduling problem. Based on the results, the most important solver parameters are identified. It is shown that by tuning a very limited number of parameters, speed-ups of 60% and more can be achieved.

关键词： Hyperparameter optimization SMAC irace mixed integer linear programming SCIP Electric vehicles

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Performance analysis of mixed integer linear programming with Wavelength Division Multiplexing 2

Performance analysis of Mixed Integer Linear Programming wit...

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2nd International Conference on Devices, Circuits and Systems (ICDCS)

作者： Vinolee, R. Bhaskar, Vidhyacharan SRM Univ Dept Elect & Commun Engn Kattankulathur Tamil Nadu India

ISBN: (纸本)9781479913565

Wavelength division multiplexing network is a method to improve capacity of transmission and to design the best path between the source and destination and assign the wavelength to the path for data transmission. A simple node is to be designed with mixed integer linear programming /GPLK 4.4 as the mathematical problem formulation for the single-hop and virtual hop of the network. Comparison of the topologies, INTERNET, EON and National Science Foundation Network (NSFNET) With Wavelength Division Multiplexing Conversion having different light-path flows is made for different number of nodes with capacity and average Ingress, Egress and groomed traffic. The performance metrics is determined by Wavelength of Light paths, single hop path, Number of Virtual hops, Network Congestion, Number of Wavelength per link, and Wavelength channel capacity.

关键词： mixed integer linear programming Virtual topology Wavelength division Multiplexing Routing and Wavelength Assignment

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Temporal Pattern Localization using mixed integer linear programming 24

Temporal Pattern Localization using Mixed Integer Linear Pro...

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24th International Conference on Pattern Recognition (ICPR)

作者： Zhao, Rui Schalk, Gerwin Ji, Qiang RPI ECSE Dept Troy NY 12180 USA NYS Dept Hlth Wadsworth Ctr Albany NY USA

ISBN: (纸本)9781538637883

In this paper, we consider the problem of localizing the subsequence in time series which contains the dynamic pattern of interest. This is motivated by brain computer interface application where we need to analyze the dynamic pattern of brain signals in response to external stimulus. We treat the localization as a binary label assignment problem and formalize a mixed integer linear programming (MILP) problem. The optimal solution is obtained by minimizing a cost function associated with label assignment subject to empirical constraints induced by data acquisition process. We first experiment with synthetic data to evaluate the effectiveness of the proposed MILP formulation and achieve 10.8 % improvement on F-1-score. We then experiment with electrocorticographic (ECoG) data for a classification task and achieve 8.8 % improvement on accuracy using subsequences localized by our method compared to other methods.

关键词： Time series analysis Hidden Markov models Data collection Optimization Probabilistic logic mixed integer linear programming Pattern recognition

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Energy Resources Scheduling in Energy Communities: A comparison between mixed integer linear programming and Hybrid-adaptive Differential Evolution with decay function

Energy Resources Scheduling in Energy Communities: A compari...

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2023 IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2023

作者： Gomes, Eduardo Pereira, Lucas Morais, Hugo ITI LARSyS INESC-ID Instituto Superior Técnico-IST Universidade de Lisboa Portugal

ISBN: (纸本)9798350396782

With the ever growing number of technologies that interact with the grid, optimization and control strategies become critical to ensure the quality of service without disruption. This work analyses the application of two operational planning optimization methods, mixed integer linear programming (MILP) and Hybrid-adaptive Differential Evolution with decay function (HyDE-DF) metaheuristic, applied to an Energy Community including generation, consumption flexibility, energy storage systems, electric vehicles with vehicle-to-grid capability and the electricity exchange with the main network, with the aim of minimizing operation costs. Throughout this work, differences between approaches are highlighted, as well as considerations for each method to help convergence and improve solution quality. Both methods achieve comparable operation costs, 159.3330 and 153.4883 for MILP and HyDE-DF, respectively. © 2023 European Union.

关键词： Electric Vehicles Energy Communities Hybrid-adaptive Differential Evolution Metaheuristics mixed integer linear programming

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Container Scheduling in Kubernetes Clusters Using a mixed integer linear programming Approach 15

Container Scheduling in Kubernetes Clusters Using a Mixed In...

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15th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops, ICUMT 2023

作者： Martins, Camilla De Souza Moura, Pedro Nuno De Lucena, Sidney C. Vieira Campos, Carlos Alberto Rio de Janeiro Brazil

ISBN: (纸本)9798350393286

A large part of the services provided on the Internet resides in virtualized environments of 'cloud' providers, whose IT infrastructures adopt, for the most part, the containers virtualization technique to house the various applications that must run independently and isolated. The management of such containers predominantly adopts the Kubernetes solution, whose standard algorithm for allocating containers on physical machines (nodes) is not capable of optimizing the cost/performance ratio of the cloud environment. As a solution to this problem, this work proposes a mixed integer linear programming approach based on the Capacitated Facility Location Problem to optimize the distribution of containers in nodes of a Kubernetes cluster, taking into account the cost of installing a new node, the history of failures of the nodes in operation and the consumption of resources by each application running in a container. The experimental results show that the proposed approach significantly improves the performance of Kubernetes cluster concerning the conventional scheduling strategy while ensuring the efficient execution of applications demands. © 2023 IEEE.

关键词： Container Scheduling Facility Location Problem Kubernetes mixed integer linear programming

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Using mixed integer linear programming with Stochastic Models for Monte Carlo Investment Analysis in the District Heating Sector

Using Mixed Integer Linear Programming with Stochastic Model...

引用

作者： Laakso, Juhana Aalto University

学位级别：硕士

The energy sector is transitioning from heavy reliance on fossil fuels to focus on renewable energy production. This transition requires decarbonization of district heating. For Fortum, one of the largest heat producers in the world, this is an important strategic focus. To achieve decarbonization of district heating systems in a profitable and low risk way, advanced tools for decision making and risk analysis are required. To answer for this need, this thesis aims to investigate how advanced MILP models created with the Fortum MONA tool can be used in a Monte Carlo simulation-based investment analysis process. To capture uncertainties in key input variables as accurately as possible, stochastic models for temperature and electricity spot prices are developed. An investment analysis process is created and tested by conducting a case study on a large heat pump investment in the Fortum Espoo district heating system. The results of the case study indicate that the developed investment analysis process succeeds in conveying a comprehensive view on investment risk and profitability, and that MONA models can successfully be used in this type of analysis. However, multiple challenges are identified, which must be overcome in order for the analysis process to be taken into wide use in Fortum. The greatest challenges are related to computation time and issues with local processing. To tackle these challenges, it is recommended that in the future, cloud computing should be utilized to run the process. In addition, development of more stochastic models for uncertain variables is suggested, in order to capture all relevant uncertainties related to an investment.

关键词： Monte Carlo simulation investment analysis district heating stochastic modelling mixed integer linear programming

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