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Energy efficiency of data center operating practices: Server clustering, powering on/off, and bang-bang control

NETWORKS 2018年第2期71卷 107-119页

作者： Cho, Yongkyu Ko, Young Myoung Pohang Univ Sci & Technol Dept Ind & Management Engn Pohang 37673 Gyeongbuk South Korea

Data centers today account for up to 3% of all global electricity consumption and produce 200 million metric tons of CO 2 . Hence, improving energy efficiency is an important operational concern. This article examines common operating practices such as server clustering, powering on/off, and bang-bang control in terms of energy efficiency. Extending the mixed integer programming (MIP) formulation in a previous research study, we introduce new constraints reflecting the operating practices adopted for operational convenience. We develop an algorithmic strategy for constructing energy efficient clusters of servers using two upper bounds on the cluster size. Numerical experiments show that server clustering and bang-bang control do not diminish energy efficiency, and that powering on/off by itself is insufficient. Our results produce a conclusion that differs from the published literature on data center design and operations. (c) 2017 Wiley Periodicals, Inc. NETWORKS, Vol. 71(2), 107-119 2018

关键词： data center operating practices energy efficiency mixed integer programming server clustering powering on off bang-bang control

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An Online Algorithm for Task Offloading in Heterogeneous Mobile Clouds

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ACM TRANSACTIONS ON INTERNET TECHNOLOGY 2018年第2期18卷 23-23页

作者： Zhou, Bowen Dastjerdi, Amir Vahid Calheiros, Rodrigo N. Buyya, Rajkumar Univ Melbourne Melbourne Vic Australia Univ Melbourne Sch Comp & Informat Syst Cloud Comp & Distributed Syst Lab Melbourne Vic Australia PricewaterhouseCoopers London England Western Sydney Univ Sch Comp Engn & Math Sydney NSW Australia

Mobile cloud computing is emerging as a promising approach to enrich user experiences at the mobile device end. Computation offloading in a heterogeneous mobile cloud environment has recently drawn increasing attention in research. The computation offloading decision making and tasks scheduling among heterogeneous shared resources in mobile clouds are becoming challenging problems in terms of providing global optimal task response time and energy efficiency. In this article, we address these two problems together in a heterogeneous mobile cloud environment as an optimization problem. Different from conventional distributed computing system scheduling problems, our joint offloading and scheduling optimization problem considers unique contexts of mobile clouds such as wireless network connections and mobile device mobility, which makes the problem more complex. We propose a context-aware mixed integer programming model to provide off-line optimal solutions for making the offloading decisions and scheduling the offloaded tasks among the shared computing resources in heterogeneous mobile clouds. The objective is to minimize the global task completion time (i.e., makespan). To solve the problem in real time, we further propose a deterministic online algorithm-the Online Code Offloading and Scheduling (OCOS) algorithm-based on the rent/buy problem and prove the algorithm is 2-competitive. Performance evaluation results show that the OCOS algorithm can generate schedules that have around two times shorter makespan than conventional independent task scheduling algorithms. Also, it can save around 30% more on makespan of task execution schedules than conventional offloading strategies, and scales well as the number of users grows.

关键词： Mobile cloud computing code offloading mixed integer programming online scheduling

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A TWO-STAGE ROBUST METHOD FOR FLEXIBLE INTEGRATED MASTER SURGICAL SCHEDULING AND CASE-MIX PLANNING

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INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING-THEORY APPLICATIONS AND PRACTICE 2022年第1期29卷 47-65页

作者： Barafkandeh, Shayan Atighehchian, Arezoo Kianfar, Kamran Univ Isfahan Fac Engn Dept Ind Engn & Futures Studies Esfahan Iran

This paper investigates the integrated master surgical scheduling and case-mix planning problem with the objective of a weighted sum of minimizing the costs of overtime and idle time, increasing surgeons' preferences, and reducing uncovered demands. Considering the uncertainty in surgery demands, a robust optimization model is proposed. A two-stage method is designed for creating and updating this scheduling with respect to downstream resources. The first stage allocates the time blocks to each surgeon integrated with determining the mix of surgery types assigned to each block. In the second stage, having the weekly waiting list of patients, the schedule is updated on the weekly horizon to cope with demand fluctuations and to maximize the use of operating rooms capacity. The proposed method is validated using real data from a teaching hospital in Iran. The results of the proposed models significantly outperformed the real plan of a hospital, which indicated the efficiency of the designed models. Comparing the deterministic and robust models shows that robust models lead to better results in over 70% of the test instances.

关键词： Master Surgical Scheduling Case-mix Planning mixed integer programming Robust Optimization

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Power distribution network configuration applying the corridor method

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COMPUTERS & INDUSTRIAL ENGINEERING 2023年 186卷

作者： Geri, Alberto Maccioni, Marco Meloni, Carlo Nati, Ludovico Palazzoli, Alessandro Sapienza Univ Roma Dipartimento Ingn Astronaut Elettr & Energet Rome Italy Sapienza Univ Roma Dipartimento Ingn Informat Automat & Gest Antonio Rome Italy Areti SpA Rome Italy

In this paper, an optimization scheme based on the Corridor Method (CM) matheuristic is proposed for power distribution network configuration with the objective of client balancing between feeders. The problem is formulated as a mixed integer optimization problem (MIP) referring to a variant of the constrained spanning forest problem on a network. The problem is classified as NP-complete in its decision version, and the proposed matheuristic optimization approach is aimed to find high quality solutions in a short computational time on large real instances. According to the characteristics of the power distribution networks, suitable modeling solutions are adopted to retain a radial structure, satisfy power flow and voltage constraints, and reduce the reconfiguration efforts requiring a limited number of maneuvers on the electrical network. Computational experiments on different instances related to a real network have been conducted. The results demonstrated the soundness and the effectiveness of the proposed solution with respect to a baseline represented by a MIP formulation solved by a state-of-the-art commercial solver: the scalability towards large-size cases has been also considered. These results show that the proposed configuration method can effectively and efficiently solve the considered problem giving adequate support to the decision-makers.

关键词： mixed integer programming Matheuristics Power distribution networks Corridor method Constrained spanning forest

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Multi-resource collaborative scheduling problem of automated terminal considering the AGV charging effect under COVID-19

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OCEAN & COASTAL MANAGEMENT 2023年 232卷 106422页

作者： Sun, Baofeng Zhai, Gaoshuai Li, Shi Pei, Bin Jilin Univ Coll Transportat Changchun 130022 Peoples R China China FAW Grp Corp Mfg Dept Changchun 130013 Peoples R China China FAW Grp Corp Engn & Mfg Logist Dept Changchun 130013 Peoples R China

Since the COVID-19 ravaged the global terminals, the Automated Container Terminal (ACT) has become one of important approach to promote the stronger quick response capacity to deal with the uncertainty that COVID-19 brought to the terminal. This research takes Automated Guided Vehicle (AGV) and their effects into account the multi-resource collaborative scheduling model to tradeoff ACT operational efficiency and energy savings. Firstly, the dual-cycle strategy of QC and the pooling strategy of AGV are given, which coordinates the scheduling of Quay Cranes (QCs), Yard Cranes (YCs) and other equipment. Furthermore, a multi-resource collaborative scheduling optimization model is proposed which roots from the principle of the Blocking-type Hybrid Flow Shop Problem (B-HFSP) with the objectives of minimizing the makespan of QC and the transportation energy consumption. And simultaneously, a mixed algorithm SA-GA is designed for solving this mixed integer programming model by an optimizing effect of Simulated Annealing on Genetic algorithms. Numerical experiments show that the model in this research is effective. The convergence of SA-GA is effective for small-scale cases and superior for large-scale cases. Considering both goals of high efficiency and energy saving, the Pareto solution set and collaborative scheduling solution take a priority to ensure that the bottlenecked QC runs efficiently. Here and now the average idle rate of QC is about [14%, 35%] lower than that of other equipment. The collaborative scheduling model constructed above not only has reference value for other multi-device and multi-stage scheduling problem, but also enhance the integrated decision-making ability of the ACT in the post-epidemic era.

关键词： Automated container terminal Scheduling Dual-cycle HFSP mixed integer programming

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An optimization model and traffic light control scheme for heterogeneous traffic systems

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TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2021年 124卷 102911-102911页

作者： Zhang, Yicheng Su, Rong Inst Infocomm Res I2R 1 Fusionopolis Way21-01 Connexis Singapore 138632 Singapore Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore ASTAR Inst Infocomm Res I2R 1 Fusionopolis Way21-01 Connexis Singapore 138632 Singapore

In this paper, one type of heterogeneous traffic network, which consists of signalized intersections and non-signalized ones, is analyzed and modelled with a macroscopic model and logic constraints, which involves the evolution of the number of vehicles on each link and the leaving flow dynamics at each intersection. We propose a novel model describing the dynamic behaviors of such a system and the proposed model is validated via road tests in Singapore traffic network and simulations in VISSIM. A piecewise linear model is adopted to describe the traffic flow dynamics at each signalized intersection, while a platooning-like first-in-first-out (FIFO) model is proposed to depict the dynamics at each non-signalized intersection. A traffic light control problem for a heterogeneous traffic network is formulated based on the proposed macroscopic model as a mixed integer programming problem. Simulations indicate that the proposed optimal traffic control scheme could outperform the fixed-time traffic light control strategy and conventional actuated traffic light control scheme. Besides, we demonstrate potentials in developing a systematic planning approach on deciding which traffic intersections require signal control to ensure good traffic control performance.

关键词： Macroscopic modelling Heterogeneous systems mixed integer programming Traffic light control

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Two-stage no-wait hybrid flow shop with inter-stage flexibility for operating room scheduling

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COMPUTERS & INDUSTRIAL ENGINEERING 2022年 168卷

作者： Azaiez, Mohamed-Naceur Gharbi, Anis Kacem, Imed Makhlouf, Yosra Masmoudi, Malek Univ Tunis Tunis Business Sch Business Analyt & DEcis Making Lab BADEM Tunis 2059 Tunisia King Saud Univ Coll Engn Dept Ind Engn Riyadh 11421 Saudi Arabia Univ Lorraine LCOMS 3 Rue Augustin Fresnel Metz France Univ Sharjah Coll Engn Sharjah U Arab Emirates

Operating rooms are amongst the most critical resources in hospitals. Appropriate schedules of surgical interventions increase the surgeries' success rates. Indeed, surgery outcomes strongly depend on the timing of each step in the surgery process. Therefore, effective and efficient surgery schedules can ease patients' suffering and even save their lives while making good use of limited hospital resources. This paper studies the two-stage nowait hybrid flow shop scheduling problem with inter-stage flexibility. The problem is inspired from hospital operating room scheduling under limited healthcare resources. We propose a time-indexed mixed integer linear programming formulation of the problem. We also introduce valid inequalities along with four lower bounds and four heuristics to handle the large scale of the problem. The proposed model is tested on randomly generated instances based on realistic data for operating room scheduling. Experimental results on the performance of the model and comparisons among the lower bounds and heuristics are reported for the different sizes of instance classes.

关键词： Hybrid flow shop mixed integer programming Time-indexed formulation Lower bounds Heuristics Valid inequalities

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Research on Optimization of Charge Batch Planning Based on Augmented Lagrangian Relaxation Algorithm

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IFAC-PapersOnLine 2019年第1期52卷 814-819页

作者： Congxin Li Baolong Yuan Junhua Ren Liangliang Sun Juan Wang School of Information and Control Engineering Shenyang Jianzhu University Shenyang China School of Architecture and Urban Planning Shenyang Jianzhu University Shenyang China

The steelmaking-continuous casting batch planning plays an important role in the relationship between the Enterprise Resource Planning (ERP) layer and the Manufacturing Execution System (MES) layer. The charge batch planning is one of the important links in the steelmaking-continuous casting batch planning. Efficient optimization of charge batch planning can reduce energy consumption and improve the profit of the enterprise. As the production scale of iron and steel enterprises increases, the number of orders increases exponentially, and the optimization goal becomes more and more complicated, which makes it difficult to ensure the optimization efficiency while ensuring the quality of optimization results. Aiming at this problem, this paper proposes a multi-performance index mixed integer programming model considering actual production, and solves it based on the order decomposition strategy under the linearized Augmented Lagrangian framework. Finally, experiments show that the proposed algorithm can effectively improve the compilation efficiency and quality of the charge batch planning compared with the traditional Lagrangian Relaxation algorithm.

关键词： charge batch planning orders mixed integer programming Augmented Lagrangian framework

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Branch and Bound Algorithm for Optimal Sensor Network Design

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IFAC Proceedings Volumes 2013年第32期46卷 690-695页

作者： Govind Menon M. Nabil Sridharakumar Narasimhan Indian Institute of Technology Madras Chennai 600 036 India

The sensor network design procedure developed by Nabil and Narasimhan (2012), which relates process economics and data reconciliation, involves the formulation of a mixed integer cone program. The solution to this problem yields the globally optimal sensor network. A branch and bound method can be used to find the global optimum; however, for systems with large numbers of variables, this approach may require a large amount of computational effort to find the solution. In this paper, a specialized branch and bound algorithm is proposed for solving the sensor network design problem, which uses certain heuristics to obtain a solution faster. One involves a low rank factorization to reduce the size of the relaxed problem. The other involves an approximation of the global lower bound for the branch and bound solution. The utility of this algorithm is demonstrated on a simple flow network, a small but realistic evaporator system, and a medium sized steam metering network.

关键词： Measurement selection mixed integer programming global optimum data reconciliation operational loss

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Design of Cellular Manufacturing Systems Considering Dynamic Production Planning and Worker Assignments

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Journal of Mathematics and System Science 2016年第1期6卷 1-15页

作者： Tariq Aljuneidi Akif A. Bulgak Department of Mechanical and Industrial Engineering Coneordia University 1455 de Maisonneuve Blvd. West Montreal Quebec H3G 1M8 Canada.

This article presents a comprehensive mathematical model for the design and analysis of Dynamic Cellular Manufacturing Systems （DCMS）. The proposed DCMS model considers several manufacturing attributes such as multi period production planning, dynamic system reconfiguration, duplicate machines, machine capacity, the available time for workers, worker assignments, and machine procurement. The objective is to minimize total costs; consisting of holding cost, outsourcing cost, inter-cell material handling cost, maintenance and overhead cost, machine relocation cost. While a study of published articles in the area of Cellular Manufacturing Systems （CMS） shows that workforce management issues have not sufficiently been addressed in the literature, the model presented also incorporates CMS workforce management issues such as salaries, hiring and firing costs of workers in addition to the manufacturing attributes. In-depth discussions on the results for two numerical examples are presented to illustrate applications of the proposed model. The model developed aims to raise the envelope by expanding and improving several CMS models previously presented in the literature.

关键词： Facilities planning and design Cellular Manufacturing Systems mixed integer programming Production Planning Worker Assignments.

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