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A multi-period mixed integer linear programming model for water and energy supply planning in Kuwait

CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY 2015年第2期17卷 485-499页

作者： AlQattan, Nael Ross, Mark Sunol, Aydin K. Univ S Florida Coll Engn Tampa FL 33620 USA

The demand for water often necessitates desalination, particularly in arid coastal environments. Desalination is often integrated with electrical cogeneration. The demands for water and electricity change over time and are subject to uncertainty. A country-wide large-scale energy and water cogeneration planning model for Kuwait is formulated as a multi-period mixed integer linear programming problem and solved to minimize the net present value over the time period of 2013-2050. Five different plant technology options were considered for desalination and cogeneration including Oil & Multi Stage Flash, Natural Gas & Multi-Effect Distillation, Natural Gas & Reverse Osmosis, Solar Energy & Multi-Effect Distillation, and Solar Energy & Reverse Osmosis. Both water and energy usage in Kuwait and data from existing plants were utilized in providing the parameters and forecasts necessary for solution of the mathematical programming model. The model provides technology choice and associated capacity decisions for existing plants, new plants at green sites, and existing plant capacity expansions as well as their timing to meet the demands.

关键词： Cogeneration mixed integer linear programming Capacity expansion Desalination

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A mixed integer linear programming approach to schedule the operating room

A mixed integer linear programming approach to schedule the ...

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IEEE International Conference on Systems, Man, and Cybernetics

作者： F. MAAROUFI H. CAMUS O. KORBAA MARS équipe OSS ENSI Manouba Manouba Tunisia LAGIS équipe OSL Ecole Centrale de Lille Villeneuve d'Ascq France MARS équipe OSS ISITCom Hamam Sousse Sousse Tunisia

ISBN: (纸本)9781509018987

the problem studied in this paper is to allocate and to sequence the elective operation on operating rooms (ORs). We develop a mixed integer linear programming (MILP) model to solve this problem. Decisions in this model include the allocation of operations to material resources and human resources, the starting time of them and the starting time for each surgeon. To show the efficiency of this model, we decide to compare it with a constraints programming (CP) approach. The performance of these models is tested using a benchmark of the literature. The results indicate the efficiency of the MILP model compared with the CP model in terms of computational time.

关键词： constraint programming health care operating rooms mixed integer linear programming

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The Planning of Distribution Network Containing Distributed Generators Based on mixed integer linear programming 5

The Planning of Distribution Network Containing Distributed ...

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5th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT)

作者： Shi, Jinyue Qiao, Ying Wang, Yingrui Wen, Junqiang Tong, Jingjing Zhang, Jianhua North China Elect Power Univ Sch Elect & Elect Engn Beijing Peoples R China

ISBN: (纸本)9781467371063

currently, the methods for solving the planning of distribution network (DN) are meta-heuristic algorithms whose computational efficiency is low and the results are not accurate. Therefore, this paper uses the advanced mixed integer linear programming (MILP) technology to model the multi-conductor DN planning containing the allocation of distributed generator (DG). Firstly, replace power flow calculation with an equivalent cone programming, then remove the product terms of binary and continuous variables, and finally use polyhedral models which are linear to approximate the planning model. In addition, as the siting and sizing of DG are added to the network planning, the situation that part of the loads are supplied by the DG separately perhaps appear thus leading to the appearance of loops. So the spanning tree (ST) constraints are introduced to the model to ensure the radiation of the DN. Finally, 23-node distribution system is used to simulate the above-mentioned model, and the results show the effectiveness and efficiency of the proposed model.

关键词： distributed generator mixed integer linear programming distribution network planning multi-conductor planning spanning tree constraints

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Smart Residential Energy Scheduling Utilizing Two Stage mixed integer linear programming

Smart Residential Energy Scheduling Utilizing Two Stage Mixe...

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North American Power Symposium (NAPS)

作者： Amini, M. H. Frye, Justin Ilic, Marija D. Karabasoglu, O. Carnegie Mellon Univ Dept Elect & Comp Engn Pittsburgh PA 15213 USA Sun Yat Sen Univ Carnegie Mellon Univ Joint Inst Pittsburgh PA USA Delft Univ Technol Fac Technol Policy & Management Delft Netherlands Shunde Int SYSU CMU Joint Res Inst Shunde Guangdong Peoples R China

ISBN: (纸本)9781467373890

In this paper, we design and evaluate the feasibility of a system which minimizes residential electricity cost of individual homes by shifting demand over a daily forecast price cycle. Ideally, our system will accept use-time preferences from consumers and optimize their appliances' operation around those given patterns. However, using the system to recommend optimum use-times to consumers is also possible by accepting ideal use preferences from an external load manager and computing the cost savings of these preferences relative to the cost of the consumer's current use patterns. We implement the optimization problem in two stages by using mixed integer linear programming (MILP). In the first stage, we obtain the optimum scheduling for appliances to be connected to the outlet;the output of this stage only shows the hours that we can use the appliance and does not reflect the actual consumption hours of each appliance. In the second stage, we model the random behavior of users via Monte Carlo simulation by running the appliances within the times they receive power, specified in the first stage. Finally, we evaluate the effectiveness of the proposed model in terms of cost savings by considering three appliances and four pricing schemes.

关键词： Monte Carlo methods domestic appliances integer programming linear programming pricing MILP Monte Carlo simulation optimum scheduling pricing scheme residential electricity cost minimization smart residential energy scheduling two stage mixed integer linear programming Home appliances Load management Mathematical model Optimization Pricing Real-time systems Schedules Appliances Monte Carlo technique Pricing load management real-time systems integer programming linear programming Mathematical Model Consumers mixed integer linear programming cost analysis double-stage

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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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mixed integer linear programming Models for Selecting Ground-Level Ozone Control Strategies

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ENVIRONMENTAL MODELING & ASSESSMENT 2014年第6期19卷 503-514页

作者： Hsu, Wei-Che Rosenberger, Jay M. Sule, Neelesh V. Sattler, Melanie L. Chen, Victoria C. P. Univ Texas Arlington Dept Ind & Mfg Syst Engn Arlington TX 76019 USA Providence Engn & Environm Grp Irving TX 75038 USA Univ Texas Arlington Dept Civil Engn Arlington TX 76019 USA

The traditional strategy for ground-level ozone control is to apply emission reductions across the board throughout certain time periods and locations. In this paper, we study various mixed integer linear programming (MILP) models that seek to select targeted control strategies for the Dallas Fort-Worth (DFW) region to reduce emissions, in order to achieve the State Implementation Plan (SIP) requirements with minimum cost. Statistics and optimization methods are used to determine a potential set of cost-effective control strategies for reducing ozone. These targeted control strategies are specified for different types of emission sources in various time periods and locations. Three MILP models, a static model, a sequential model, and a dynamic model, are studied in this research. These different MILP models allow decision makers to study how the targeted control strategies change under different circumstances. Meanwhile, two types of auxiliary variables are considered as supplemental control strategies in the optimization if the current set of control strategies is unable to reduce ozone to complywith the 8-h ozone standard. Results fromthe differentmodels can provide decisionmakers with information concerning how the effectiveness of the control strategies varies with daily emission patterns and meteorology.

关键词： mixed integer linear programming Control strategies Auxiliary variables Ground-level ozone

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Model Predictive Control of Central Chiller Plant With Thermal Energy Storage Via Dynamic programming and mixed-integer linear programming

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2015年第2期12卷 565-579页

作者： Deng, Kun Sun, Yu Li, Sisi Lu, Yan Brouwer, Jack Mehta, Prashant G. Zhou, MengChu Chakraborty, Amit Univ Illinois Dept Mech Sci & Engn Urbana IL 61801 USA Siemens Corp Corp Technol Princeton NJ 08540 USA New Jersey Inst Technol Dept Elect & Comp Engn Newark NJ 07102 USA King Abdulaziz Univ Dept Elect & Comp Engn Jeddah 21413 Saudi Arabia NIST Gaithersburg MD 20899 USA Univ Calif Irvine Dept Mech & Aerosp Engn Irvine CA 92697 USA

This work considers the optimal scheduling problem for a campus central plant equipped with a bank of multiple electrical chillers and a thermal energy storage (TES). Typically, the chillers are operated in ON/OFF modes to charge TES and supply chilled water to satisfy the campus cooling demands. A bilinear model is established to describe the system dynamics of the central plant. A model predictive control (MPC) problem is formulated to obtain optimal set-points to satisfy the campus cooling demands and minimize daily electricity cost. At each time step, the MPC problem is represented as a large-scale mixed-integer nonlinear programming problem. We propose a heuristic algorithm to obtain suboptimal solutions for it via dynamic programming (DP) and mixed integer linear programming (MILP). The system dynamics is linearized along the simulated trajectories of the system. The optimal TES operation profile is obtained by solving a DP problem at every horizon, and the optimal chiller operations are obtained by solving an MILP problem at every time step with a fixed TES operation profile. Simulation results show desired performance and computational tractability of the proposed algorithm. Note to Practitioners-This work was motivated by the supervisory control need for a campus central plant. Plant operators have to decide a scheduling strategy to mix and match various chillers with a thermal energy storage to satisfy the campus cooling demands, while minimizing the operation cost. This work mathematically characterizes the system dynamics of a campus central plant and establishes a linear model to predict campus cooling load. It proposes a model predictive control (MPC) strategy to optimally schedule the campus central plant based on plant system dynamics and predicted campus cooling load. A heuristic algorithm is proposed to obtain suboptimal solutions for the MPC problem. The effectiveness and efficiency of the proposed approach are well demonstrated for the central pl

关键词： Central chiller plant dynamic programming heuristic algorithm mixed integer linear programming model predictive control supervisory control thermal energy storage

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Simultaneous signal selection for silicon debug through mixed-integer linear programming

Simultaneous signal selection for silicon debug through Mixe...

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International Conference on Emerging Trends in Engineering, Technology and Science (ICETETS)

作者： R. Agalya S. Saravanan School of Computing SASTRA University Thanjavur India

ISBN: (纸本)9781467367264

Post-silicon validation is the most vital parts of modern Integrated Circuits. The key challenge of silicon validation is that it has limited observability and controllability of internal signals. To improve those, a profitable set of signals should be selected. An automated procedure is proposed to select those signals which are used to facilitate early malfunctions of the design. Given the input vector set to the design an error transmission matrix is generated. From that, both relatively independent and dependent flip-flops are identified for grouping the signals through mixed-integer linear programming. This method precisely identifies the paths which improves observability and can speed up the process.

关键词： Observability Computer bugs Silicon Flip-flops Controllability mixed integer linear programming linear programming

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mixed-integer linear programming for Multibeam Satellite Systems Design: Application to the Beam Layout Optimization

Mixed-Integer Linear Programming for Multibeam Satellite Sys...

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Annual IEEE International Systems Conference

作者： Jean-Thomas Camino Christian Artigues Laurent Houssin Stephane Mourgues Airbus Defence and Space Space Systems Telecommunication Systems Department CNRS LAAS

ISBN: (纸本)9781467395205

In a society where the demand for multimedia applications and data exchange is experiencing an unstoppable growth, multibeam systems have proven to be one of the most relevant solutions for satellite-based communication systems. Though already well represented among the geostationary satellites today, there are still several unresolved design optimization challenges for these complex systems that could lead to improved performances and to better system costs. The satellite platform, the repeater, and the antennas are examples of subsystems that should be designed jointly in order to reach an optimized technical solution that fulfills the service requirements. Traditionally, such complex tasks are addressed through a decomposition of the overall system design into a sequence of smaller decision problems. In this article, we propose to rely on operations research techniques to, on the one hand, take into account explicitly the interdependencies of these decomposed problems, and on the other hand, to handle the own constraints of each subsystem and their interactions. In this paper, the focus is laid on the optimization of the beam layouts of the multibeam satellites. Indeed, in addition to being a perfect example of the aforementioned importance of dealing with subsystem constraints, this problem appears early in the chain of design of a multibeam satellite system and is therefore critical for the quality of the telecommunication system;the weaknesses of a beam layout cannot be made up for later on in the system design. For this crucial optimization phase, the strength of the methodology we propose in this paper is to use mixed-integer linear programming to incorporate explicitly technological feasibility constraints of the subsystems involved, while preparing at best the subsequent design problems. Most importantly, our approach allows to overcome several resisting flaws of the already existing algorithms.

关键词： Satellite Telecommunications Systems Design mixed-integer linear programming Operations Research Operations Research SUB-SYSTEM System design mixed integer linear programming Satellite communication systems engineering Satellite systems layouts Telecommunication systems Satellite platforms integer linear programming Beams and girders

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Inter-sample avoidance in trajectory optimizers using mixed-integer linear programming

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INTERNATIONAL JOURNAL OF ROBUST AND NONlinear CONTROL 2015年第4期25卷 521-526页

作者： Richards, Arthur Turnbull, Oliver Univ Bristol Dept Aerosp Engn Bristol Avon England Univ Bristol Dept Aerosp Engn Bristol Avon England

This paper proposes an extension to trajectory optimization using mixed-integer linear programming. The purpose of the extension is to ensure that avoidance constraints are respected at all times between discrete samples, not just at the sampling times themselves. The method is very simple and involves applying the same switched constraints at adjacent time steps. This requires fewer additional constraints than the existing approach and is shown to reduce computation time. A key benefit of efficient inter-sample avoidance is the facility to reduce the number of time steps without having to compensate by enlarging the obstacles. A further extension to the principle is presented to account for curved paths between samples, proving useful in cases where narrow passageways are traversed. Copyright (c) 2013 John Wiley & Sons, Ltd.

关键词： trajectory optimization mixed integer linear programming collision avoidance

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