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Improvement of Real-time Traffic Management by Using Optimization Tools

Procedia - Social and Behavioral Sciences 2014年 160卷 465-473页

作者： Joaquín Rodriguez Paola Pellegrini Grégory Marlière Shaowei Hu Sonia Sobieraj Richard University Lille Nord de France IFSTTAR 20 rue Élisée Reclus BP 70317 59666 Villeneuve d’Ascq Cedex France

Railway operation management must cope with failures of the railway system or external disturbances that may cause initial delays or so-called primary delays. In heavy traffic areas of rail networks, primary delays can quickly propagate and lead to the so-called secondary or knock-on delays. This paper describes the results of experiments done to evaluate railway traffic optimization tools that enable to decrease the secondary delays by selecting appropriate route settings and sequence of the train movements. These experiments are part of a task of the European FP7 project ON-TIME. The project aims to develop a prototype for a new generation of railway traffic management systems which will increase capacity and decrease delays for railway customers’ satisfaction. The results of the project will be validated through system simulation and real-life case studies proposed by railway undertakings which are partners of the project. This paper focuses on the results achieved in one of the case studies of the ON-TIME project, through an algorithm which we developed. It consists of the solution of a mixed-integer linear programming formulation for a limited computation time: the best feasible solution found within this limited computation time is the final solution returned by the algorithm. The case study tackled here represents traffic in the Gonesse junction, in France. We assess the impact of including the optimization in a rolling-horizon framework. The results show that the optimization is quite robust to different settings of the rolling-horizon framework.

关键词： railway traffic management routing scheduling mixed integer linear programming rolling-horizon

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Model predictive control for optimization of combined heat and electric power microgrid

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IFAC Proceedings Volumes 2014年第3期47卷 2201-2206页

作者： G. Gambino F. Verrilli D. Meola M. Himanka G. Palmieri C. Del Vecchio L. Glielmo Department of Engineering University of Sannio Benevento Italy Centria University of Applied Sciences Kokkola Finland

This is a contribution to the economic dispatch problem of combined electrical and heat power microgrids. A mixed integer linear microgrid model has been developed; the microgrid operations optimization problem has been formulated using mixed-integer linear programming and Model Predictive Control technique has been applied to take system uncertainties into account. The proposed optimization algorithm has been applied to a tertiary site microgrid, located in Finland; the obtained numerical results have been compared with a heuristic algorithm.

关键词： Optimization Model Predictive Control micro grids mixed integer linear programming

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Flow Merging and Hub Route Optimization in Collaborative Transportation

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JOURNAL OF APPLIED MATHEMATICS 2014年第unknown期2014卷 1-8页

作者： Weng, Kerui Xu, Zi-hao China Univ Geosci Sch Econ & Management Wuhan 430074 Peoples R China

This paper studies the optimal hub routing problem of merged tasks in collaborative transportation. This problem allows all carriers' transportation tasks to reach the destinations optionally passing through 0, 1, or 2 hubs within limited distance, while a cost discount on arcs in the hub route could be acquired after paying fixed charges. The problem arises in the application of logistics, postal services, airline transportation, and so forth. We formulate the problem as a mixed-integer programming model, and provide two heuristic approaches, respectively, based on Lagrangian relaxation and Benders decomposition. Computational experiments show that the algorithms work well.

关键词： MATHEMATICAL optimization PROBLEM solving HEURISTIC algorithms mixed integer linear programming LOGISTICS management

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Evaluation of Power Saving and Feasibility Study of Migrations Solutions in a Virtual Router Network

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JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING 2014年第unknown期2014卷 1-14页

作者： Eramo, V. Testa, S. Miucci, E. Sapienza Univ Rome Dept Informat Engn Elect & Telecommun I-00184 Rome Italy

The power consumption of the network equipment has increased significantly and some strategies to contain the power used in the IP network are needed. Among the green networking strategies, the virtualization class and in particular the deployment of migrating virtual routers can lead to a high energy saving. It consists in migrating virtual routers in fewer physical nodes when the traffic decreases allowing for a power consumption saving. In this paper we formulate the problem of minimizing the power consumption as a mixed integer linear programming ( MILP) problem. Due to the hard complexity of the introduced MILP problem, we propose a heuristic for the migration of virtual routers among physical devices in order to turn off as many nodes as possible and save power according to the compliance with network node and link capacity constraints. We show that 50% of nodes may be turned off in the case of a real provider network when traffic percentage reduction of 80% occurs. Finally we also perform a feasibility study by means of an experimental test-bed to evaluate migration time of a routing plane based on QUAGGA routing software.

关键词： COMPUTER networks ENERGY consumption ENERGY conservation FEASIBILITY studies ROUTERS (Computer networks) mixed integer linear programming INTERNET protocols

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Optimal ILP-Based Approach for Gate Location Assignment and Scheduling in Quantum Circuits

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MODELLING AND SIMULATION IN ENGINEERING 2014年第1期2014卷 1-8页

作者： Mohammadzadeh, Naser Bahreini, Tayebeh Badri, Hossein Shahed Univ Comp Engn Dept Tehran Iran Amirkabir Univ Technol Dept Ind Engn Tehran Iran

Physical design and synthesis are two key processes of quantum circuit design methodology. The physical design process itself decomposes into scheduling, mapping, routing, and placement. In this paper, a mathematical model is proposed for mapping, routing, and scheduling in ion-trap technology in order to minimize latency of the circuit. The proposed model which is a mixed integer linear programming (MILP) model gives the optimal locations for gates and the best sequence of operations in terms of latency. Experimental results show that our scheme outperforms the other schemes for the attempted benchmarks.

关键词： GATE array circuits OPTIMAL designs (Statistics) QUANTUM theory mixed integer linear programming MATHEMATICAL models COMPUTER scheduling

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Achieving Fair Spectrum Allocation and Reduced Spectrum Handoff in Wireless Sensor Networks: Modeling via Biobjective Optimization

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MODELLING AND SIMULATION IN ENGINEERING 2014年第1期2014卷 1-12页

作者： Byun, Sang-Seon Kansanen, Kimmo Balasingham, Ilangko Gil, Joon-Min Catholic Univ Pusan Dept Comp Engn Busan South Korea Norwegian Univ Sci & Technol Dept Elect & Telecommun Trondheim Norway Oslo Univ Hosp Rikshosp Oslo Norway Catholic Univ Daegu Sch Informat Technol Engn Gyongsan Gyeongbuk South Korea

This paper considers the problem of centralized spectrum allocations in wireless sensor networks towards the following goals: (1) maximizing fairness, (2) reflecting the priority among sensor data, and (3) avoiding unnecessary spectrum handoff. We cast this problem into a multiobjective mixed integer nonconvex nonlinear programming that is definitely difficult to solve at least globally without any aid of conversion or approximation. To tackle this intractability, we first convexify the original problem using arithmetic-geometric mean approximation and logarithmic change of the decision variables and then deploy weighted Chebyshev norm-based scalarization method in order to collapse the multiobjective problem into a single objective one. Finally, we apply simple rounding method in order to obtain approximate integer solutions. The results obtained from the numerical experiments show that, by adjusting the weight on each objective function, the proposed algorithm allocates spectrum bands fairly with well observing each sensor's priority and reduced spectrum handoffs.

关键词： WIRELESS sensor networks ROAMING (Telecommunication) SPECTRUM allocation mixed integer linear programming NONlinear programming APPROXIMATION algorithms

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Optimized Buffer Allocation in Multicore Platforms 14

Optimized Buffer Allocation in Multicore Platforms

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Design, Automation and Test in Europe Conference and Exhibition

作者： Maximilian Odendahl Andres Goens Rainer Leupers Gerd Ascheid Benjamin Ries Berthold Vocking Tomas Henriksson RWTH Aachen University Aachen Germany Huawei Technologies Stockholm Sweden

ISBN: (纸本)9783981537024

With the availability of advanced MPSoC and emerging Dynamic RAM (DRAM) interface technologies, an optimal allocation of logical data buffers to physical memory cannot be handled manually anymore due to the huge design space. An allocation does not only need to decide between an on-or off-chip memory, but also needs to take an increasing number of available memory channels, different bandwidth capacities and several routing possibilities into account. We formalize this problem and introduce a mixed integer linear programming (MILP) model based on two different optimization criteria. We implement the MILP model into a retargetable tool and present a case study with representative data of the Long-Term-Evolution (LTE) standard to show the real-life applicability of our approach.

关键词： buffer allocation Physical Memory optimal criterion Multi-core processors mixed integer linear programming Dynamic random access storage Platform

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Implementation of price-based demand response programs through a load pattern clustering process

Implementation of price-based demand response programs throu...

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MedPower 2014

作者： I.P. Panapakidis S.I. Frantza G.K. Papagiannis Aristotle University of Thessaloniki Thessaloniki GR

ISBN: (纸本)9781510814097

This study addresses the problem of the optimal design of price-based Demand Response (DR) programs such as Real-Time Pricing (RTP) utilizing the load profiling tool. The proposed model corresponds to a profit maximization problem of a retailer that serves a group of residential consumers. Through a clustering process the consumers are grouped together in several clusters. For each cluster a dynamic tariff is offered that is specially design to fit to the typical load pattern of the cluster. The sensitivity of the demand over the offered selling price is modeled through a price responsive demand function. Apart from implementing different demand functions, the flexibility of the proposed model offers a selection of different clustering algorithms and different retailer pricing policy.

关键词： Demand Response Load Profiling mixed-integer Nonlinear programming Retailer Profit Maximization Demand-Responsive load pattern clustering process Clustering algorithms mixed integer linear programming

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Day-ahead microgrid optimal self-scheduling: Comparison between three methods applied to isolated DC microgrid

Day-ahead microgrid optimal self-scheduling: Comparison betw...

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Annual Conference of the IEEE Industrial Electronics Society

作者： Leonardo Trigueiro Dos Santos Manuela Sechilariu Fabrice Locment AVENUES-GSU EA 7284 Universite de Technologie de Compiegne

ISBN: (纸本)9781479940318

This paper presents three different methods to optimize a day-ahead self-scheduling for an isolated DC microgrid operation. Based on forecast data, a multi-objective cost function is formulated aiming to minimize the total energy cost by reducing the micro-turbine fuel consumption, avoiding photovoltaic power limitation and load shedding, while respecting the storage parameters and microgrid operation constraints. The problem is solved with two different optimization algorithms and one rule-based algorithm. The comparison is made on the total energy cost and computational cost for each proposed approach. The results prove that the mixed integer linear programing optimization permits to obtain the lower total energy cost with a reasonable computational cost.

关键词： Microgrid Optimization Differential evolution mixed integer linear programming Rule-based algorithm Photovoltaic systems Energy storage Micro-turbine

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Receding Horizon Control for Demand-Response Operation of Building Heating Systems

Receding Horizon Control for Demand-Response Operation of Bu...

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IEEE Annual Conference on Decision and Control

作者： Gianni Bianchini Marco Casini Antonio Vicino Donato Zarrilli Dipartimento di Ingegneria dell'Informazione e Scienze Matematiche Universita di Siena Via Roma 56 53100 Siena Italy

ISBN: (纸本)9781467360890

In this paper we consider the problem of optimizing the operation of a building heating system under the hypothesis that the building is included as a consumer in a Demand Response program. Demand response requests to the building are assumed to come from an external market or grid operator. The requests assume the form of price/volume signals specifying a volume of energy to be saved during a given time slot and a monetary reward assigned to the participant in case it fulfills the conditions. A receding horizon control approach is adopted for minimization of the energy bill, by exploiting a simplified model of the building. Since the resulting optimization problem is a mixed integer linear programming problem which turns out to be manageable only for buildings with very few zones, a heuristic is devised to make the algorithm applicable to realistic size problems as well. The derived control law is tested on the realistic simulator EnergyPlus to evaluate pros and cons of the proposed algorithm. The performance of the suboptimal control law is evaluated by comparison with the optimal one on a chosen test case.

关键词： Buildings space heating (buildings) mixed integer linear programming control law Horizon CASING INSPECTION Surgery

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