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A mixed integer linear programming solution for single hoist multi-degree cyclic scheduling with reentrance

ENGINEERING OPTIMIZATION 2014年第5期46卷 704-723页

作者： Li, Xin Fung, Richard Y. K. City Univ Hong Kong Dept Syst Engn & Engn Management Hong Kong Hong Kong Peoples R China

This article considers single hoist multi-degree cyclic scheduling problems with reentrance. Time window constraints are also considered. Firstly, a mixed integer programming model is formulated for multi-degree cyclic hoist scheduling without reentrance, referred to as basic lines in this article. Two valid inequalities corresponding to this problem are also presented. Based on the model for basic lines, an extended mixed integer programming model is proposed for more complicated scheduling problems with reentrance. Phillips and Unger's benchmark instance and randomly generated instances are applied to test the model without reentrance, solved using the commercial software CPLEX. The efficiency of the model is analysed based on computational time. Moreover, an example is given to demonstrate the effectiveness of the model with reentrance.

关键词： hoist scheduling problems mixed integer linear programming multi-degree cycle reentrance robotic cells

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An Effective Problem Decomposition Method for Scheduling of Diffusion Processes Based on mixed integer linear programming

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IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING 2014年第3期27卷 357-363页

作者： Jung, Chihyun Pabst, Detlef Ham, Myoungsoo Stehli, Marcel Rothe, Marcel GLOBALFOUNDRIES Inc Malta NY 12020 USA Liberty Univ Sch Engn & Computat Sci Lynchburg VA 24515 USA GLOBALFOUNDRIES Inc D-10109 Dresden Germany

Diffusion processes in semiconductor fabrication facilities (Fabs) refer to the series of processes from wafer cleaning processes to furnace processes. Most furnace tools are batch tools, with large batch sizes, and have relatively long process times, when compared to the other processes. Strict time window constraints link cleaning processes with furnace processes for quality control. Those operational requirements for diffusion processes make their scheduling very difficult. This paper proposes an advanced scheduling approach based on a rolling horizon scheduling concept. Due to the combinatorial nature of the scheduling problem, the complexity of the problem increases exponentially, when the number of jobs and tools increase. However, the computation time allowed for the scheduler is limited in practice, because the variability in most Fabs requires schedulers to update the schedule in short intervals. We suggest an mixed integer linear programming model for diffusion processes, and propose an effective decomposition method to deal with this complexity problem. The decomposition method repeats multiple scheduling iterations, as it gradually extends the number of runs on tools, enabling the scheduler to generate near-optimal schedules in limited time intervals. The scheduler could make large improvements on key performance indicators, such as time window violation rates, batch sizes, throughput, etc. The software architecture of the scheduler implementation is also addressed in this paper.

关键词： Diffusion processes scheduling batch tools time window constraints mixed integer linear programming decomposition method

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Feature selection for Support Vector Machines via mixed integer linear programming

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INFORMATION SCIENCES 2014年 279卷 163-175页

作者： Maldonado, Sebastian Perez, Juan Weber, Richard Labbe, Martine Univ Los Andes Santiago Chile Univ Chile Dept Ind Engn Santiago Chile Univ Libre Bruxelles Dept Comp Sci B-1050 Brussels Belgium

The performance of classification methods, such as Support Vector Machines, depends heavily on the proper choice of the feature set used to construct the classifier. Feature selection is an NP-hard problem that has been studied extensively in the literature. Most strategies propose the elimination of features independently of classifier construction by exploiting statistical properties of each of the variables, or via greedy search. All such strategies are heuristic by nature. In this work we propose two different mixed integer linear programming formulations based on extensions of Support Vector Machines to overcome these shortcomings. The proposed approaches perform variable selection simultaneously with classifier construction using optimization models. We ran experiments on real-world benchmark datasets, comparing our approaches with well-known feature selection techniques and obtained better predictions with consistently fewer relevant features. (C) 2014 Elsevier Inc. All rights reserved.

关键词： Feature selection Support Vector Machine mixed integer linear programming

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A branch and bound method for the solution of multiparametric mixed integer linear programming problems

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JOURNAL OF GLOBAL OPTIMIZATION 2014年第2-3期59卷 527-543页

作者： Oberdieck, Richard Wittmann-Hohlbein, Martina Pistikopoulos, Efstratios N. ETH Inst Chem & Bioengn Dept Chem & Appl Biosci CH-8093 Zurich Switzerland Univ London Imperial Coll Sci Technol & Med Ctr Proc Syst Engn Dept Chem Engn London SW7 2BY England

In this paper, we present a novel algorithm for the solution of multiparametric mixed integer linear programming (mp-MILP) problems that exhibit uncertain objective function coefficients and uncertain entries in the right-hand side constraint vector. The algorithmic procedure employs a branch and bound strategy that involves the solution of a multiparametric linear programming sub-problem at leaf nodes and appropriate comparison procedures to update the tree. McCormick relaxation procedures are employed to overcome the presence of bilinear terms in the model. The algorithm generates an envelope of parametric profiles, containing the optimal solution of the mp-MILP problem. The parameter space is partitioned into polyhedral convex critical regions. Two examples are presented to illustrate the steps of the proposed algorithm.

关键词： Multiparametric programming mixed integer linear programming Branch and bound

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Thyristor-Controlled Switch Capacitor Placement in Large-Scale Power Systems via mixed integer linear programming and Taylor Series Expansion

Thyristor-Controlled Switch Capacitor Placement in Large-Sca...

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IEEE PES General Meeting

作者： Ziaee, Omid Choobineh, F. Fred Univ Nebraska Dept Elect Engn Lincoln NE 68588 USA

ISBN: (纸本)9781479964154

Allocation of flexible alternating current transmission system (FACTS) devices to an electric power transmission network may be formulated as a nonlinear mathematical program. Solving such a nonlinear program for a large transmission network is computationally very expensive, and obtaining the optimal solution may be impossible. We present a Taylor series expansion approximation of the nonlinearities of the problem and propose a mixed integer linear program (MILP) for finding the optimum location and proper settings of a Thyristor-Controlled Series Capacitor (TCSC) in an electric power network. The objective of this problem is to minimize total generation cost based on the DC load flow model. The proposed method is implemented for the 118-bus IEEE test case and the results are discussed.

关键词： Flexible AC Transmission System DC optimal power flow mixed integer linear programming Taylor series expansion generation cost

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linear or mixed integer programming in long-term energy systems modeling - A comparative analysis for a local expanding heating system

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ENERGY 2023年 283卷

作者： Vilen, Karl Ahlgren, Erik O. Chalmers Univ Technol Dept Space Earth & Environm Div Energy Technol SE-41396 Gothenburg Sweden

Most computer models used in energy systems optimization modeling studies are formulated using linear equations. However, since linear formulations do not always well reflect real-world conditions, they may not always be adequate as policy and support tools. This is particularly the case for local system studies attempting to represent technologies at the individual scale, as in the case for local heating system modeling. Thus, the aim of this paper is to investigate differences in the resulting heating solutions and model solution times for a local expanding heating system. Three different investment cost structures for individual and district heating solutions for the heating of new housing are investigated using linear and mixed integer linear programming. The results show that the use of district heating is higher for the cost structures that use mixed integer linear programming than it is for the linear cost structures. This result is attributed mainly to the fact that individual air-to-water heat pumps benefit from the linear equation formulation due to its high coefficient of performance during summertime. This finding is important to consider when modeling local energy systems. The solution time is, however, significantly shorter for the linear formulations than for the mixed integer linear formulations.

关键词： Housing District heating Local energy system modeling TIMES mixed integer linear programming linear programming

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Volt/Var Optimization of Unbalanced Distribution Feeders via mixed integer linear programming

Volt/Var Optimization of Unbalanced Distribution Feeders via...

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2014 Power Systems Computation Conference (PSCC)

作者： Borghetti, Alberto Napolitano, Fabio Nucci, Carlo Alberto Univ Bologna Dept Elect Elect & Informat Engn Bologna Italy

ISBN: (纸本)9788393580132

The paper presents a mixed integer linear programming (MILP) model for the solution of the three-phase volt/var optimization (VVO) of medium voltage unbalanced distribution feeders. The VVO of a distribution feeder is aimed at calculating the most efficient operating conditions by means of the scheduling of transformers equipped with an on-load tap changer and distributed reactive power resources (such as embedded generators and switchable capacitors banks). The proposed model allows the representation of feeders composed by three-phase, two-phase, and single-phase lines, by transformers with different winding connections, by unbalanced wye- and delta-connected loads, by three-phase and single phase capacitor banks and embedded generators. The accuracy of the results is verified by using IEEE Test Feeders.

关键词： power distribution feeders unbalanced networks volt/var optimization mixed integer linear programming

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Performance analysis of mixed integer linear programming with Wavelength Division Multiplexing 2

Performance analysis of Mixed Integer Linear Programming wit...

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2nd International Conference on Devices, Circuits and Systems (ICDCS)

作者： Vinolee, R. Bhaskar, Vidhyacharan SRM Univ Dept Elect & Commun Engn Kattankulathur Tamil Nadu India

ISBN: (纸本)9781479913565

Wavelength division multiplexing network is a method to improve capacity of transmission and to design the best path between the source and destination and assign the wavelength to the path for data transmission. A simple node is to be designed with mixed integer linear programming /GPLK 4.4 as the mathematical problem formulation for the single-hop and virtual hop of the network. Comparison of the topologies, INTERNET, EON and National Science Foundation Network (NSFNET) With Wavelength Division Multiplexing Conversion having different light-path flows is made for different number of nodes with capacity and average Ingress, Egress and groomed traffic. The performance metrics is determined by Wavelength of Light paths, single hop path, Number of Virtual hops, Network Congestion, Number of Wavelength per link, and Wavelength channel capacity.

关键词： mixed integer linear programming Virtual topology Wavelength division Multiplexing Routing and Wavelength Assignment

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Optimal Microgrid Component Sizing using mixed integer linear programming

Optimal Microgrid Component Sizing using Mixed Integer Linea...

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IEEE Transportation Electrification Conference and Expo (ITEC)

作者： Yu, Xiang Eric Malysz, Pawel Sirouspour, Shahin Emadi, Ali McMaster Univ Hamilton ON L8S 4L8 Canada

ISBN: (纸本)9781479956159

This paper proposes a novel method for determining the optimal number of renewable energy and storage components in a microgrid given typical load profiles, local pricing regime, and capital costs. Case studies using solar panels and advanced lead acid battery modules are performed under residential, commercial, and off-grid sites. Simple mixed integer linear programming (MILP) optimization problems are formulated, presented, and solved in each scenario where economic analysis highlights the utility of the proposed approach.

关键词： Batteries Economics Electricity Microgrids Optimization Pricing mixed integer linear programming MICRO-GRID Pricing Batteries Electricity economics component sizing Solar collectors

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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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