检索结果-内蒙古大学图书馆

Modeling and Solution of the Large-Scale Security-Constrained Unit Commitment

IEEE TRANSACTIONS ON POWER SYSTEMS 2013年第4期28卷 3524-3533页

作者： Fu, Yong Li, Zuyi Wu, Lei Mississippi State Univ Dept Elect & Comp Engn Mississippi State MS 39759 USA IIT Dept Elect & Comp Engn Chicago IL 60616 USA Clarkson Univ Dept Elect & Comp Engn Potsdam NY 13699 USA

Security-constrained unit commitment (SCUC), as one of key components in power system operation, is being widely applied in vertically integrated utilities and restructured power systems. The efficient solution framework is to implement iterations between a master problem (unit commitment) and subproblems (network security evaluations). In industrial applications, both Lagrangian relaxation and mixed-integer programming are commonly applied for the unit commitment problem, and both linear sensitivity factor and Benders cut methods are used to generate additional constraints in the phase of network security evaluations. This paper evaluates capabilities and performances of each algorithm through technical discussion and numerical testing. Special topics on the large-scale SCUC engine development are also discussed in this paper, such as input data screening, inactive constrains elimination, contingency management, infeasibility handling, parallel computing, and model simplification. This paper will benefit academic researchers, software developers, and system operators when they design, develop and assess effective models and algorithms for solving large-scale SCUC problems.

关键词： Benders decomposition Lagrangian relaxation linear sensitivity factors mixed-integer programming security-constrained unit commitment (SCUC)

来源：评论

学校读者我要写书评

暂无评论

Solving fuzzy p-hub center problem by genetic algorithm incorporating local search

引用

APPLIED SOFT COMPUTING 2013年第5期13卷 2624-2632页

作者： Yang, Kai Liu, Yan-Kui Yang, Guo-Qing Hebei Univ Coll Math & Comp Sci Risk Management & Financial Engn Lab Baoding 071002 Hebei Peoples R China

The p-hub center problem has extensive applications in various real-world fields such as transportation and telecommunication systems. This paper presents a new risk aversion p-hub center problem with fuzzy travel times, in which value-at-risk (VaR) criterion is adopted in the formulation of objection function. For trapezoidal and normal fuzzy travel times, we first turn the original VaR p-hub center problem into its equivalent parametric mixed-integer programming problem, then develop a hybrid algorithm by incorporating genetic algorithm and local search (GALS) to solve the parametric mixed-integer programming problem. In our designed GALS, the GA is used to perform global search, while LS strategy is applied to each generated individual (or chromosome) of the population. Finally, we conduct two sets of numerical experiments and discuss the experimental results obtained by general-purpose LINGO solver, standard GA and GALS. The computational results show that the GALS achieves the better performance than LINGO solver and standard GA. (C) 2012 Elsevier B. V. All rights reserved.

关键词： p-Hub center problem Fuzzy travel time mixed-integer programming Genetic algorithm Local search

来源：评论

学校读者我要写书评

暂无评论

Multiple and nonuniform time grids in discrete-time MIP models for chemical production scheduling

引用

COMPUTERS & CHEMICAL ENGINEERING 2013年 53卷 70-85页

作者： Velez, Sara Maravelias, Christos T. Univ Wisconsin Dept Chem & Biol Engn Madison WI 53706 USA

The modeling of time plays a key role in the formulation of mixed-integer programming (MIP) models for scheduling, production planning, and operational supply chain planning problems. It affects the size of the model, the computational requirements, and the quality of the solution. While the development of smaller continuous-time scheduling models, based on multiple time grids, has received considerable attention, no truly different modeling methods are available for discrete-time models. In this paper, we challenge the long-standing belief that employing a discrete modeling of time requires a common uniform grid. First, we show that multiple grids can actually be employed in discrete-time models. Second, we show that not only unit-specific but also task-specific and material-specific grids can be generated. Third, we present methods to systematically formulate discrete-time multi-grid models that allow different tasks, units, or materials to have their own time grid. We present two different algorithms to find the grid. The first algorithm determines the largest grid spacing that will not eliminate the optimal solution. The second algorithm allows the user to adjust the level of approximation;more approximate grids may have worse solutions, but many fewer binary variables. Importantly, we show that the proposed models have exactly the same types of constraints as models relying on a single uniform grid, which means that the proposed models are tight and that known solution methods can be employed. The proposed methods lead to substantial reductions in the size of the formulations and thus the computational requirements. In addition, they can yield better solutions than formulations that use approximations. We show how to select the different time grids, state the formulation, and present computational results. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Chemical production scheduling Modeling of time mixed-integer programming

来源：评论

学校读者我要写书评

暂无评论

A simulation-based approach to price optimisation of the mixed bundling problem with capacity constraints

引用

INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2013年第2期145卷 584-598页

作者： Mayer, Stefan Klein, Robert Seiermann, Stephanie Univ Augsburg Chair Analyt & Optimizat D-86159 Augsburg Germany

In this paper, we analyse a service provider's mixed bundling problem for services such as sporting events or holiday packages. Pursuing the objective of maximising total revenue, the service provider has to determine static prices for each single product at the beginning of the selling period. Additionally, an optimal package price has to be chosen for the bundle that comprises one unit of each single product. Because of capacity constraints, the availability of products can change over time such that consumers are forced to switch from their preferred subset of products to an alternative following dynamic substitution. We propose two mixed-integer linear programmes based on reservation prices that appropriately model the consumer choice process to address the bundling problem. It becomes evident that the determination of the optimal prices is computationally expensive even for small problem classes. Therefore, we develop metaheuristics using variable neighbourhoods. To evaluate their performance, we propose the following new approach: our extensive computational study is performed using especially generated scenarios for which the optimal product prices are known. For this purpose, we present a set of conditions for the generation of reservation prices that guarantee the optimality of the predefined prices. Based on our computational results, managerial insights are derived. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Pricing Bundling mixed-integer programming Metaheuristics VNS

来源：评论

学校读者我要写书评

暂无评论

Hybrid soft computing algorithmic framework for smart home energy management

引用

SOFT COMPUTING 2013年第11期17卷 1983-2005页

作者： Severini, Marco Squartini, Stefano Piazza, Francesco Univ Politecn Marche Dept Informat Engn 3MediaLabs I-60131 Ancona Italy

Energy management in Smart Home environments is undoubtedly one of the pressing issues in the Smart Grid research field. The aim typically consists in developing a suitable engineering solution able to maximally exploit the availability of renewable resources. Due to the presence of diverse cooperating devices, a complex model, involving the characterization of nonlinear phenomena, is indeed required on purpose. In this paper an Hybrid Soft Computing algorithmic framework, where genetic, neural networks and deterministic optimization algorithms jointly operate, is proposed to perform an efficient scheduling of the electrical tasks and of the activity of energy resources, by adequately handling the inherent nonlinear aspects of the energy management model. In particular, in order to address the end-user comfort constraints, the home thermal characterization is needed: this is accomplished by a nonlinear model relating the energy demand with the required temperature profile. A genetic algorithm, based on such model, is then used to optimally allocate the energy request to match the user thermal constraints, and therefore to allow the mixed-integer deterministic optimization algorithm to determine the remaining energy management actions. From this perspective, the ability to schedule the tasks and allocate the overall energy resources over a finite time horizon is assessed by means of diverse computer simulations in realistic conditions, allowing the authors to positively conclude about the effectiveness of the proposed approach. The degree of realism of the simulated scenario is confirmed by the usage of solar energy production forecasted data, obtained by means of a neural-network based algorithm which completes the framework.

关键词： Smart home energy management Task and energy resource scheduling Thermal comfort mixed-integer programming Soft computing Genetic algorithm Neural networks Smart grid

来源：评论

学校读者我要写书评

暂无评论

Locally ideal formulations for piecewise linear functions with indicator variables

引用

OPERATIONS RESEARCH LETTERS 2013年第6期41卷 627-632页

作者： Sridhar, Srikrishna Linderoth, Jeff Luedtke, James Univ Wisconsin Sch Comp Sci Madison WI 53706 USA Univ Wisconsin Dept Ind & Syst Engn Madison WI 53706 USA

In this paper, we consider mixed integer linear programming (MIP) formulations for piecewise linear functions (PLFs) that are evaluated when an indicator variable is turned on. We describe modifications to standard MIP formulations for PLFs with desirable theoretical properties and superior computational performance in this context. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Piecewise linear function mixed-integer programming Indicator variables

来源：评论

学校读者我要写书评

暂无评论

On parallelizing dual decomposition in stochastic integer programming

引用

OPERATIONS RESEARCH LETTERS 2013年第3期41卷 252-258页

作者： Lubin, Miles Martin, Kipp Petra, Cosmin G. Sandikci, Burhaneddin Argonne Natl Lab Math & Comp Sci Div Argonne IL 60439 USA Univ Chicago Booth Sch Business Chicago IL 60637 USA

For stochastic mixed-integer programs, we revisit the dual decomposition algorithm of Came and Schultz from a computational perspective with the aim of its parallelization. We address an important bottleneck of parallel execution by identifying a formulation that permits the parallel solution of the master program by using structure-exploiting interior-point solvers. Our results demonstrate the potential for parallel speedup and the importance of regularization (stabilization) in the dual optimization. Load imbalance is identified as a remaining barrier to parallel scalability. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Stochastic programming mixed-integer programming Column generation Dual decomposition Parallel computing Bundle methods

来源：评论

学校读者我要写书评

暂无评论

Backdoor Branching

引用

INFORMS JOURNAL ON COMPUTING 2013年第4期25卷 693-700页

作者： Fischetti, Matteo Monaci, Michele Univ Padua Dept Informat Engn I-35131 Padua Italy

We present an exact mixed-integer programming (MIP) solution scheme where a set-covering model is used to find a small set of first-choice branching variables. In a preliminary "sampling" phase, our method quickly collects a number of relevant low-cost fractional solutions that qualify as obstacles for the linear programming (LP) relaxation bound improvement. Then a set covering model is solved to detect a small subset of variables (a "backdoor," in the artificial intelligence jargon) that "cover the fractionality" of the collected fractional solutions. These backdoor variables are put in a priority branching list, and a black-box MIP solver is eventually run-in its default mode-by taking this list into account, thus avoiding any other interference with its highly optimized internal mechanisms. Computational results on a large set of instances from the literature are presented, showing that some speedup can be achieved even with respect to a state-of-the-art solver such as IBM ILOG CPLEX 12.2.

关键词： mixed-integer programming branch and bound computational analysis

来源：评论

学校读者我要写书评

暂无评论

Site selection of emergency material warehouse under fuzzy environment

引用

Journal of Central South University 2013年第6期20卷 1610-1615页

作者：刘诚陈则辉龚玉燕 School of Mathematics and Statistics Central South University

The objective of this work was to determine the location of emergency material warehouses. For the site selection problem of emergency material warehouses, the triangular fuzzy numbers are respectively demand of the demand node, the distance between the warehouse and demand node and the cost of the warehouse, a bi-objective programming model was established with minimum total cost of the system and minimum distance between the selected emergency material warehouses and the demand node. Using the theories of fuzzy numbers, the fuzzy programming model was transformed into a determinate bi-objective mixed integer programming model and a heuristic algorithm for this model was designed. Then, the algorithm was proven to be feasible and effective through a numerical example. Analysis results show that the location of emergency material warehouse depends heavily on the values of degree a and weight wl. Accurate information of a certain emergency activity should be collected before making the decision.

关键词： bi-objective mixed-integer programming emergency material warehouse triangular fuzzy number site selection

来源：评论

学校读者我要写书评

暂无评论

Solving a reverse supply chain design problem by improved Benders decomposition schemes

引用

COMPUTERS & INDUSTRIAL ENGINEERING 2013年第4期66卷 889-898页

作者： Santibanez-Gonzalez, Ernesto D. R. Diabat, Ali Univ Fed Ouro Preto Dept Comp Ouro Preto MG Brazil Masdar Inst Sci & Technol Dept Engn Syst & Management Abu Dhabi U Arab Emirates

In this paper we propose improved Benders decomposition schemes for solving a remanufacturing supply chain design problem (RSCP). We introduce a set of valid inequalities in order to improve the quality of the lower bound and also to accelerate the convergence of the classical Benders algorithm. We also derive quasi Pareto-optimal cuts for improving convergence and propose a Benders decomposition scheme to solve our RSCP problem. Computational experiments for randomly generated networks of up to 700 sourcing sites, 100 candidate sites for locating reprocessing facilities, and 50 reclamation facilities are presented. In general, according to our computational results, the Benders decomposition scheme based on the quasi Pareto-optimal cuts outperforms the classical algorithm with valid inequalities. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Supply chain management Reverse logistics Benders decomposition mixed-integer programming

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：