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13th Global Congress on Manufacturing and Management (GCMM)

作者： Cao, Wujun Zhang, Mengzhuo Zhengzhou Univ Sch Management Engn 100 Kexue Rd High Tech Dev Zone Zhengzhou 450001 Peoples R China

This paper studies the scheduling problem about the Automatic Vehicle Storage and Retrieval System controlling of the shuttle combined vehicles and the elevator to complete the storing and picking-up operations on the order in automatic three-dimensional warehouse. For the order with the pure storing operations or pure picking-up operations, it directly solve them similar to Traveling Salesman Problem( TSP), and for storing and picking-up compound operations, it will respectively cooperate and schedule the elevator with one or two sets of shuttle combined vehicles to complete the task in the shortest time. Pertinent mathematical models has been established, and have been simulated and optimized with MATLAB. Compared with the conventional random access strategy, the current method can greatly save the travel time of the elevator and shuttle bus. The lower time consumption and higher efficiency indicates that the method presented is of significant value in both theory and practical usage. (C) 2017 The Authors. Published by Elsevier Ltd.

关键词： Automated three-dimensional warehouse shuttle combined vehicles optimization and scheduling genetic algorithm

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The optimization and scheduling Research of Shuttle Combined Vehicles in Automatic Three-dimensional Warehouse

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Procedia Engineering 2017年 174卷 579-587页

作者： Wujun Cao Mengzhuo Zhang School of Management Engineering Zhengzhou University NO.100 Kexue Road High-Tech Development Zone Zhengzhou 450001 P.R. China

This paper studies the scheduling problem about the Automatic Vehicle Storage and Retrieval System controlling of the shuttle combined vehicles and the elevator to complete the storing and picking-up operations on the order in automatic three-dimensional warehouse. For the order with the pure storing operations or pure picking-up operations, it directly solve them similar to Traveling Salesman Problem (TSP), and for storing and picking-up compound operations,it will respectively cooperate and schedule the elevator with one or two sets of shuttle combined vehicles to complete the task in the shortest time. Pertinent mathematical models has been established, and have been simulated and optimized with MATLAB. Compared with the conventional random access strategy, the current method can greatly save the travel time of the elevator and shuttle bus. The lower time consumption and higher efficiency indicates that the method presented is of significant value in both theory and practical usage.

关键词： Automated three-dimensional warehouse shuttle combined vehicles optimization and scheduling genetic algorithm

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optimization techniques for task scheduling criteria in IaaS cloud computing atmosphere using nature inspired hybrid spotted hyena optimization algorithm

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2022年第24期34卷

作者： Natesan, Gobalakrishnan Ali, Javid Krishnadoss, Pradeep Chidambaram, Raman Nanjappan, Manikandan Sri Venkateswara Coll Engn Dept Informat Technol Chennai Tamil Nadu India St Josephs Inst Technol Dept Informat Technol Chennai Tamil Nadu India Vellore Inst Technol Sch Comp Sci & Engn Chennai Tamil Nadu India St Josephs Coll Engn Dept Informat Technol Chennai Tamil Nadu India SRM Inst Sci & Technol Dept Data Sci & Business Syst Kancheepuram Tamil Nadu India

Cloud computing has garnered unprecedented growth in recent years in the field of Information Technology. It has emerged as a high-performance computing option owing to its infrastructure that comprises of heterogeneous collection of autonomous computers and adaptable network architecture. The tasks that are scheduled in an optimized manner for their execution could be classified under NP-hard problems. Though meta-heuristic scheduling algorithms emerge as scheduling options, they need to be much more consistent while dealing with the dynamic set up of the cloud environment. In this paper, we had proposed a multi-objective meta-heuristic scheduling algorithm namely Quasi Oppositional Genetic Spotted Hyena optimization (QOGSHO) algorithm that globally optimizes the makespan, resource consumption and SLA violation QoS parameters, thereby improving the performance. The algorithm proposed is an amalgamated product of meta-heuristic algorithms like Quasi Oppositional Based Learning (QOBL), Spotted Hyena optimization (SHO), and Genetic Algorithm (GA). The performance efficiency of the proposed QOGSHO algorithm had been compared with various scheduling algorithms using uniform datasets by varying the data instance sizes in a simulated cloud environment. The obtained results clearly justify the task scheduling efficiency of the proposed algorithm with respect to the QoS parameters namely makespan, resource utilization and SLA violation.

关键词： cloud computing meta-heuristic optimization and scheduling QoS parameters

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Optimized flexibility management enacting Data Centres participation in Smart Demand Response programs

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2018年 78卷 330-342页

作者： Cioara, Tudor Anghel, Ionut Bertoncini, Massimo Salomie, Loan Arnone, Diego Mammina, Marzia Velivassaki, Terpsichori-Helen Antal, Marcel Tech Univ Cluj Napoca Comp Sci Baritiu 26 Cluj Napoca Romania Tech Univ Cluj Napoca Distributed Syst Res Lab Baritiu 26 Cluj Napoca Romania Tech Univ Cluj Napoca Baritiu 26 Cluj Napoca Romania Engn Ingn Informat Via SM della Battaglia 56 Rome Italy Singular Log Al Panagouli & Siniosoglou Athens Greece

In this paper we address the problem of Data Centres (DCs) integration into the Smart Grid scenario by proposing a technique for scheduling and optimizing their operation allowing them to participate in Smart Demand Response programs. The technique is leveraging on DCs available flexible energy resources, on mechanisms for eliciting this latent flexibility and on an innovative electronic marketplace designed for trading energy flexibility and ancillary services. This will enact DCs to shape their energy demand to buy additional energy when prices are low and sell energy surplus when prices are high. At the same time DCs will be able to provide increased energy demand due to a large un-forecasted renewable energy production in their local grid, shed or shift energy demand over time to avoid a coincidental peak load, provide fast ramping power by turning on their backup fossil fuelled generators and injecting the energy surplus in the grid and finally provide reactive power regulation by changing their power factor. Numerical simulations results considering traces of an operational DC indicate the great potential of the proposed technique for supporting DCs participation in Smart Demand Response programs. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Data Centre Smart Demand Response Flexible energy resources optimization and scheduling Energy and Ancillary Services Marketplace

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Thermal-aware Server Provisioning with Switched MPC for HPC Data Centers

Thermal-aware Server Provisioning with Switched MPC for HPC ...

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10th IFAC Symposium on Nonlinear Control Systems (NOLCOS)

作者： Fang, Qin Wang, Jun Gong, Qi Tongji Univ Dept Control Sci & Engn Shanghai 201804 Peoples R China Univ Calif Santa Cruz Dept Appl Math & Stat Santa Cruz CA 95064 USA

This paper aims at implementing dynamic server provisioning and thermal-aware server assignment methods to particular high-performance-computing data centers which processing a large portion of small size jobs. A hysteresis server provisioning algorithm is proposed to reactively provide extra idle servers to process unexpected incoming small size jobs. Then, we use the thermal-aware server assignment to allocate active servers to high cooling efficiency areas. To address discrete characteristics of server provisioning, a switched model predictive control approach is developed for thermal-aware active servers allocation, and for obtaining the optimal temperature set-points of the cooling system. Simulation results show that significant energy saving can be achieved.

关键词： optimization and scheduling Nonlinear Model Predictive Control Theory and Applications Switching Control

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Joint Bidding Decision of Wind Farms and Energy Storage Based on Newsvendor Model

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Journal of Systems Science and Information 2022年第1期10卷 51-64页

作者： Xinyue SUN Jian LIU Meng OU Yanyan LIU School of Economics and Management Nanjing University of Science and TechnologyNanjing 210094China

Currently,renewable energy generation has received more and more *** article focuses on wind energy generation,one of the renewable energy *** at the intermittent and unpredictable wind power problems,according to the day ahead bidding mechanism in the power market,this paper introduces the energy storage system to maximize wind power merchants profit based on the newsvendor ***,this paper focuses on the wind farms combined with storage system to put forward the optimal bidding decision of selling or buying electricity to the market one day in advance and the optimal bidding ***,we analyze the relationship between the optimal bid amount and the market penalty price coefficient,government subsidy,storage system charge and discharge efficiency,and other *** on the analysis of various parameters,power generation companies can make reasonable bidding decisions and amount to maximize profits.

关键词： wind farms energy storage optimization and scheduling newsvendor model power market

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Resilient scheduler and controller codesign for mixed-critical embedded control systems 22

Resilient scheduler and controller codesign for mixed-critic...

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22nd World Congress of the International Federation of Automatic Control (IFAC)

作者： Al Khatib, Mohammad Bajcinca, Naim Tech Univ Kaiserslautern Dept Mech & Proc Engn Kaiserslautern Germany

ISBN: (纸本)9781713872344

Designing stable embedded control systems presents challenges when limited communication and computation resources are involved. This document provides an approach to codesign a scheduler and a resilient controller for a given set of linear mixed-critical embedded control systems sharing a number of computation resources. Precisely, we are interested in optimizing control inputs and resource allocation in order to ensure control performance, resilience, and faster feedback control response for more critical tasks. The approach is based on a formulation of the problem in the form of a mixed-integer MPC problem. The latter is solved online and provide controllers with new updates, while the latest previous inputs are held constant otherwise. We demonstrate the validity of our approach on an illustrative example. Copyright (c) 2023 The Authors.

关键词： optimization and scheduling Control of Sampled Data Systems Lyapunov Methods Mixed-integer programming Event-triggered control Network control systems

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Optimal Sensing and Transmission in Energy Harvesting Sensor Networks

Optimal Sensing and Transmission in Energy Harvesting Sensor...

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作者： Wu, Xianwen University of Arkansas

学位级别：Ph.D.

Sensor networks equipped with energy harvesting (EH) devices have attracted great attentions recently. Compared with conventional sensor networks powered by batteries, the energy harvesting abilities of the sensor nodes make sustainable and environment-friendly sensor networks possible. However, the random, scarce and non-uniform energy supply features also necessitate a completely different approach to energy management. A typical EH wireless sensor node consists of an EH module that converts ambient energy to electrical energy, which is stored in a rechargeable battery, and will be used to power the sensing and transmission operations of the sensor. Therefore, both sensing and transmission are subject to the stochastic energy constraint imposed by the EH process. In this dissertation, we investigate optimal sensing and transmission policies for EH sensor networks under such constraints. For EH sensing, our objective is to understand how the temporal and spatial variabilities of the EH processes would affect the sensing performance of the network, and how sensor nodes should coordinate their data collection procedures with each other to cope with the random and non-uniform energy supply and provide reliable sensing performance with analytically provable guarantees. Specifically, we investigate optimal sensing policies for a single sensor node with infinite and finite battery sizes in Chapter 2, status updating/transmission strategy of an EH Source in Chapter 3, and a collaborative sensing policy for a multi-node EH sensor network in Chapter 4. For EH communication, our objective is to evaluate the impacts of stochastic variability of the EH process and practical battery usage constraint on the EH systems, and develop optimal transmission policies by taking such impacts into consideration. Specifically, we consider throughput optimization in an EH system under battery usage constraint in Chapter 5.

关键词： Applied sciences Energy harvesting optimization and scheduling Wireless sensor networks

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Resilient scheduler and controller codesign for mixed-critical embedded control systems

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IFAC-PapersOnLine 2023年第2期56卷 9793-9798页

作者： Mohammad Al Khatib Naim Bajcinca

关键词： optimization and scheduling Control of Sampled Data Systems Lyapunov Methods Mixed-integer programming Event-triggered control Network control systems

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