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A hybrid MILP and IPM approach for dynamic economic dispatch with valve-point effects

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2018年 97卷 290-298页

作者： Pan, Shanshan Jian, Jinbao Yang, Linfeng Guangxi Univ Coll Elect Engn Nanning 530004 Peoples R China Yulin Normal Univ Guangxi Coll & Univ Key Lab Complex Syst Optimiza Yulin 537000 Peoples R China Guangxi Univ Natl Coll Sci Nanning 530006 Peoples R China Guangxi Univ Coll Comp Elect & Informat Nanning 530004 Peoples R China

Dynamic economic dispatch with valve-point effects (DED-VPE) is a non-convex and non-differentiable optimization problem that is difficult to solve efficiently. In this paper, a hybrid approach combining mixed-integer linear programming (MILP) and the interior point method (IPM), abbreviated as MILP-IPM, is proposed to solve a DED-VPE problem in which complicated transmission loss is also included. Due to the non-differentiable nature of the DED-VPE problem, the classical derivative-based optimization methods can no longer be used. With the help of model reformulation, a differentiable non-linear programming (NLP) formulation that can be directly solved using the IPM is derived. However, if the DED-VPE problem is solved using the IPM in a single step, the optimization can easily become trapped in a poor local optimum due to its non-convex nature and multiple local minima. To obtain a better solution, an MILP method is required to solve the DED-VPE problem without transmission loss, yielding a good initial point for the IPM to improve the quality of the solution. Simulation results demonstrate the validity and effectiveness of the proposed MILP-IPM approach for solving the DED-VPE problem.

关键词： Dynamic economic dispatch Valve-point effects non-linear programming Interior point method Mixed-integer linear programming

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Energy-Aware Scheduling of Embarrassingly Parallel Jobs and Resource Allocation in Cloud

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IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 2017年第6期28卷 1607-1620页

作者： Shi, Li Zhang, Zhemin Robertazzi, Thomas SUNY Stony Brook Dept Elect & Comp Engn Stony Brook NY 11794 USA Xiaomen Univ Dept Comp Sci Xiamen 361005 Peoples R China

In cloud computing, with full control of the underlying infrastructures, cloud providers can flexibly place user jobs on suitable physical servers and dynamically allocate computing resources to user jobs in the form of virtual machines. As a cloud provider, scheduling user jobs in a way that minimizes their completion time is important, as this can increase the utilization, productivity, or profit of a cloud. In this paper, we focus on the problem of scheduling embarrassingly parallel jobs composed of a set of independent tasks and consider energy consumption during scheduling. Our goal is to determine task placement plan and resource allocation plan for such jobs in a way that minimizes the Job Completion Time (JCT). We begin with proposing an analytical solution to the problem of optimal resource allocation with pre-determined task placement. In the following, we formulate the problem of scheduling a single job as a non-linear Mixed Integer programming problem and present a relaxation with an equivalent linear programming problem. We further propose an algorithm named TaPRA and its simplified version TaPRA-fast that solve the single job scheduling problem. Lastly, to address multiple jobs in online scheduling, we propose an online scheduler named OnTaPRA. By comparing with the start-of-the-art algorithms and schedulers via simulations, we demonstrate that TaPRA and TaPRA-fast reduce the JCT by 40-430 percent and the OnTaPRA scheduler reduces the average JCT by 60-280 percent. In addition, TaPRA-fast can be 10 times faster than TaPRA with around 5 percent performance degradation compared to TaPRA, which makes the use of TaPRA-fast very appropriate in practice.

关键词： Cloud computing task scheduling resource management convex optimization non-linear programming

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Real-Time Cooperative Adaptive Robust Relay Beamforming Based on Kalman Filtering Channel Estimation

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2019年第12期18卷 5600-5612页

作者： Sadr, Mohammad Amin Maleki Ahmadian-Attari, Mahmoud Amiri, Rouhollah KN Toosi Univ Technol Fac Elect & Comp Engn Tehran 163171419 Iran Sharif Univ Technol Fac Elect Engn Tehran *** Iran

In this paper, an adaptive channel estimation algorithm is proposed for the multi-user robust relay beamforming problem. We propose a norm-bounded channel uncertainty model for all of the channels. We employ the Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF) for joint estimation of channel coefficients and beamforming weights, and propose a Markov model for source-relay and relay-destination channels as well as the beamforming weights in the relays. The channel coefficients and bemforming weights are shown to be well-estimated in order to minimize the total relays power transmission subject to worst-case signal to interference and noise ratio (SINR) criterion at each receiver. As the main contribution of this paper, we propose an adaptive method for simultaneous estimation of the beamforming weights and channel states information, and solving the associated optimization problem by estimation tools. Furthermore, we show that our algorithm outperforms the interior point based methods for non-linear optimization. In comparison to our recent work, a sub-optimal solution to the non-convex robust relay beamforming problem was provided, the proposed method has superior performance and lower complexity.

关键词： Extended Kalman filter imperfect CSI non-linear programming robust optimization UKF

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A three-level problem-centric strategy for selecting NMR precursor labeling and analytes

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METABOLIC ENGINEERING 2006年第5期8卷 491-507页

作者： Ghosh, Soumitra Grossmann, Ignacio E. Ataai, Mohammad M. Domach, Michael M. Carnegie Mellon Univ Dept Chem Engn Pittsburgh PA 15213 USA Carnegie Mellon Univ Dept Chem & Petr Engn Pittsburgh PA 15213 USA

We have developed a sequential set of computational screens that may prove useful for evaluating analyte sets for their ability to accurately report on metabolic fluxes. The methodology is problem-centric in that the screens are used in the context of a particular metabolic engineering problem. That is, flux bounds and alternative flux routings are first identified for a particular problem, and then the information is used to inform the design of nuclear magnetic resonance (NMR) experiments. After obtaining the flux bounds via MILP, analytes are first screened for whether the predicted NMR spectra associated with various analytes can differentiate between different extreme point (or linear combinations of extreme point) flux solutions. The second screen entails determining whether the analytes provide unique flux values or multiple flux solutions. Finally, the economics associated with using different analytes is considered in order to further refine the analyte selection process in terms of an overall utility index, where the index summarizes the cost-benefit attributes by quantifying benefit (contrast power) per cost (e.g., NMR instrument time required). We also demonstrate the use of an alternative strategy, the Analytical Hierarchy Process, for ranking analytes based on the individual experimentalist's-generated weights assigned for the relative value of flux scenario contrast, unique inversion of NMR data to fluxes, etc. (C) 2006 Elsevier Inc. All rights reserved.

关键词： metabolic flux analysis nuclear magnetic resonance non-linear programming global optimization E. coli

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Energy-efficient buffer allocation problem in unreliable production lines

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2021年第9-10期114卷 2871-2885页

作者： Alaouchiche, Yasmine Ouazene, Yassine Yalaoui, Farouk Univ Technol Troyes Ind Syst Optimizat Lab 12 Rue Marie CurieCS42060 F-10004 Troyes France

The buffer allocation problem (BAP) is one of the major optimization problems considered by production systems designers. The BAP is widely studied in the literature, since buffers have a great impact on improving the efficiency of production systems especially for mass production. Nevertheless, with all upcoming changes in world's economy, industrial requirements and ecological awareness, the necessity of considering energy efficiency in manufacturing systems design becomes crucial. This paper introduces the first variant of energy-efficient buffer allocation problem (EE-BAP). It addresses a novel integrated analytical method to find the best buffer allocation that optimizes both throughput and energy consumption for serial production lines with unreliable machines. A large experimental study, based on different instances well established in the literature, is carried out to analyze the relevance of the proposed method. The obtained results show that considerable energy savings with low or almost no productivity loss are allowed. The energy-efficient BAP is a novel problem that considers the complex trade-off between throughput and energy efficiency performance and introduces new perspectives of research in the field of sustainable manufacturing systems design.

关键词： Sustainable manufacturing systems Buffer allocation problem Unreliable production lines Energy consumption Throughput non-linear programming

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Buffer location and sizing to optimize cost and quality in semi-continuous manufacturing processes: Methodology and application

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IIE TRANSACTIONS 2009年第12期41卷 1035-1048页

作者： Rajaram, Kumar Tian, Zhili Univ Calif Los Angeles Anderson Sch Management Los Angeles CA 90095 USA Washington Univ John M Olin Sch Business St Louis MO 63130 USA

The problem of optimizing the location and size of buffers in semi-continuous manufacturing processes is considered. This problem is formulated as a non-linear integer program that determines the optimal buffer size for individual stages and allocates tanks to those stages in order to minimize total tank inclusion, holding, quality, process overshoot and undershoot costs. Heuristics are developed to solve the problem and bounds are derived to evaluate the quality of the heuristics. This method has been implemented at three glucose and three sorbitol production processes at a leading food processing company. This has resulted in total annual cost savings of around 6.4% or $9000 000. In addition, this work has had a significant impact on several strategic operational decisions at this company.

关键词： Process industries process design buffer location non-linear programming heuristics

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A distributed approach to capacity allocation in logical networks

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2010年第3期203卷 737-748页

作者： Costa, A. Ramakrishnan, M. Taylor, P. G. Univ Melbourne Dept Math & Stat Melbourne Vic 3010 Australia

We consider a dynamic capacity reallocation scheme in a logically fully-connected telecommunications network. We show that the problem of optimal capacity allocation can be solved in a distributed manner, an essential feature of such a scheme. Our continuous-capacity reallocation scheme can be used as a foundation for a discrete system. This is useful from the perspective of practical implementation. (C) 2009 Elsevier B.V. All rights reserved.

关键词： Capacity allocation Distributed control non-linear programming Communications networks

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Coflow Scheduling in Data Centers: Routing and Bandwidth Allocation

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IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 2021年第11期32卷 2661-2675页

作者： Shi, Li Liu, Yang Zhang, Junwei Robertazzi, Thomas Snap Inc Santa Monica CA 90405 USA Google Inc Mountain View CA 94043 USA Microsoft Redmond WA 98052 USA SUNY Stony Brook Dept Elect & Comp Engn Stony Brook NY 11794 USA

In distributed computing frameworks like MapReduce, Spark, and Dyrad, a coflow is a set of flows transferring data between two stages of a job. The job cannot start its next stage unless all flows in the coflow finish. To improve the execution performance of such a job, it is crucial to reduce the completion time of a coflow, as it can contribute more than 50 percent of the job completion time. While several coflow schedulers have been proposed, we observe that routing, as a factor greatly impacting the Coflow Completion Time (CCT), has not been well considered. In this article, we focus on the coflow scheduling problem and jointly consider routing and bandwidth allocation. We begin by providing an analytical solution to the problem of optimal bandwidth allocation with pre-determined routes. In the following, we formulate the problem of scheduling a single coflow as a non-linear Mixed Integer programming problem and present its relaxed convex optimization problem. We further propose two algorithms, CoRBA and its simplified version: CoRBA-fast that solve the single coflow scheduling problem with a joint consideration of routing and bandwidth allocation. Lastly, to address multiple coflows in online scheduling, we propose an online scheduler named OnCoRBA. By comparing with the start-of-the-art algorithms and schedulers via simulations, we demonstrate that CoRBA and CoRBA-fast reduce the CCT by 30-400 percent and the OnCoRBA scheduler reduces the average online CCT by 20-230 percent. In addition, CoRBA-fast can be hundreds times faster than CoRBA with around 8 percent performance degradation compared to CoRBA, which makes the use of CoRBA-fast very appropriate in practice.

关键词： Routing Bandwidth Schedules Channel allocation Data centers Job shop scheduling Optimal scheduling Coflow scheduling distributed computing non-linear programming convex optimization

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An integrated chance-constrained stochastic model for efficient and sustainable supplier selection and order allocation

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2018年第21期56卷 6890-6916页

作者： Moheb-Alizadeh, Hadi Handfield, Robert North Carolina State Univ Grad Program Operat Res Raleigh NC USA North Carolina State Univ Poole Coll Management Dept Business Management Raleigh NC 27695 USA

Effective allocation of scarce resources across supply chain environments is an emerging issue, as enterprises face shortfalls in raw materials, human labour, budgetary resources, equipment, energy and capacity. We consider these related objectives in designing efficient and sustainable supply networks using a multi-objective mixed-integer non-linear programming (MINLP) model for efficient and sustainable supplier selection and order allocation with stochastic demand. Our approach considers sustainability dimensions including economic, environmental and social responsibility, but also seeks to design the most efficient supply network given constraints of the supply market. Enterprise efficiency is assessed using a bi-objective data envelopment analysis (DEA) whose inputs include raw materials, current expenses and labour force capacity. The resulting model is non-convex because of the presence of bilinear terms in DEA-related constraints, so we introduce a multi-stage solution procedure that first uses piecewise McCormick envelopes (PCM) to linearise the bilinear terms. Next, we introduce a set of valid inequalities in order to improve solution time of the problem whose dimension significantly increases after being linearised. We then exploit chance constrained programming approaches to deal with stochastic demand. Finally, a single aggregated objective function is derived using a fuzzy multi-objective programming approach. A manufacturing case study demonstrates the validity of the proposed approach, and its effectiveness in designing a supply network that addresses the 'triple bottom line' of people, profit and planet that comprises many sustainability initiatives in an efficient manner.

关键词： supplier selection order allocation non-linear programming valid inequalities chance-constrained programming data envelopment analysis (DEA)

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Location of slaughterhouses under economies of scale

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2006年第2期175卷 740-750页

作者： van der Broek, John Schutz, Peter Stougie, Leen Tomasgard, Asgeir Eindhoven Univ Technol Dept Math & Comp Sci & CWI NL-1090 GB Amsterdam Netherlands Eindhoven Univ Technol Dept Math & Comp Sci & NS Travellers NL-5600 MB Eindhoven Netherlands NTNU Dept Ind Econ & Technol Management SINTEF Technol & Soc N-7491 Trondheim Norway

The facility location problem described in this paper comes from an industrial application in the slaughterhouse industry of Norway. Investigations show that the slaughterhouse industry experiences economies of scale in the production facilities. We examine a location-allocation problem focusing on the location of slaughterhouses, their size and the allocation of animals in the different farming districts to these slaughterhouses. The model is general and has applications within other industries that experience economies of scale. We present an approach based on linearization of the facility costs and Lagrangean relaxation. We also develop a greedy heuristic to find upper bounds. We use the method to solve a problem instance for the Norwegian Meat Co-operative and compare our results to previous results achieved using standard branch-and-bound in commercial software. (c) 2005 Elsevier B.V. All rights reserved.

关键词： location integer programming non-linear programming branch-and-bound economies of scale

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