检索结果-内蒙古大学图书馆

6th International Conference on Wireless Communications, Networking and Mobile Computing (WICOM)

作者： Li, Fachao Wang, Li Hebei Univ Sci & Technol Sch Econ & Management Shijiazhuang 050000 Peoples R China

ISBN: (纸本)9781424437092

Stochastic transportation problems attract much attention in many fields, such as resource allocation, production management, etc. In this paper, after analyzing how to process random constraints in chance constrained programming, propose a quasi-linear pattern based on expectation and variance, moreover, give the quasi-linear programming model of stochastic transportation problems with good operability, finally, the performance of this model is discussed through an example. All these indicate the quasi-linear programming model can solve the stochastic transportation problems briefly and effectively, so it enriches methods of stochastic transportation problems.

关键词： Stochastic transportation problems chance-constrained programming quasi-linear programming model reliability coefficient

来源：评论

学校读者我要写书评

暂无评论

Expectation and chance-constrained Models and Algorithms for Insuring Critical Paths

引用

MANAGEMENT SCIENCE 2010年第10期56卷 1794-1814页

作者： Shen, Siqian Smith, J. Cole Ahmed, Shabbir Univ Florida Dept Ind & Syst Engn Gainesville FL 32611 USA Georgia Inst Technol H Milton Stewart Sch Ind & Syst Engn Atlanta GA 30332 USA

In this paper, we consider a class of two-stage stochastic optimization problems arising in the protection of vital arcs in a critical path network. A project is completed after a series of dependent tasks are all finished. We analyze a problem in which task finishing times are uncertain but can be insured a priori to mitigate potential delays. A decision maker must trade off costs incurred in insuring arcs with expected penalties associated with late project completion times, where lateness penalties are assumed to be lower semicontinuous nondecreasing functions of completion time. We provide decomposition strategies to solve this problem with respect to either convex or nonconvex penalty functions. In particular, for the nonconvex penalty case, we employ the reformulation-linearization technique to make the problem amenable to solution via Benders decomposition. We also consider a chance-constrained version of this problem, in which the probability of completing a project on time is sufficiently large. We demonstrate the computational efficacy of our approach by testing a set of size- and-complexity diversified problems, using the sample average approximation method to guide our scenario generation.

关键词： project management integer programming reformulation-linearization technique chance-constrained programming sample average approximation

来源：评论

学校读者我要写书评

暂无评论

Stochastic optimal reactive power dispatch: Formulation and solution method

引用

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2010年第6期32卷 615-621页

作者： Hu, Zechun Wang, Xifan Taylor, Gareth Shanghai Jiao Tong Univ Dept Elect Engn Shanghai 200240 Peoples R China Xi An Jiao Tong Univ Dept Elect Engn Xian 710049 Shaanxi Peoples R China Brunel Univ Brunel Inst Power Syst Uxbridge UB8 3PH Middx England

Classical optimal reactive power dispatch (ORPD) is usually formulated as a deterministic optimization problem, such that the network structure and load power injections are known and fixed. Hence, the influences of load uncertainties and branch outages are not typically considered. This paper proposes a chance-constrained programming formulation for ORPD that considers uncertain nodal power injections and random branch outages. A solution method combining both probabilistic load flow and a genetic algorithm is proposed and demonstrated in order to solve the problem. Simulations on several test systems show that the proposed method can prevent under-compensation or over-compensation of reactive power and increase voltage security margins. These advantages are achieved with the acceptable expense of a small increase in active power loss when compared with the results of classical deterministic ORPD. Several techniques are presented in order to improve the efficiency of the proposed method and case studies demonstrate the effectiveness of the techniques. (C) 2009 Elsevier Ltd. All rights reserved.

关键词： chance-constrained programming Genetic algorithm Optimal reactive power dispatch Probabilistic load flow

来源：评论

学校读者我要写书评

暂无评论

Solving chance-constrained combinatorial problems to optimality

引用

COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 2010年第3期45卷 607-638页

作者： Klopfenstein, Olivier France Telecom R&D F-92130 Issy Les Moulineaux France Univ Technol Compiegne CNRS UMR 6599 Lab Heudiasyc F-60205 Compiegne France

The aim of this paper is to provide new efficient methods for solving general chance-constrained integer linear programs to optimality. Valid linear inequalities are given for these problems. They are proved to characterize properly the set of solutions. They are based on a specific scenario, whose definition impacts strongly on the quality of the linear relaxation built. A branch-and-cut algorithm is described to solve chance-constrained combinatorial problems to optimality. Numerical tests validate the theoretical analysis and illustrate the practical efficiency of the proposed approach.

关键词： chance-constrained programming Integer linear programming

来源：评论

学校读者我要写书评

暂无评论

Robust Dynamic Real-time Optimization under Parametric Uncertainty for Plant-wide Processes

Robust Dynamic Real-time Optimization under Parametric Uncer...

引用

8th World Congress on Intelligent Control and Automation (WCICA)

作者： Zhang, Yan Shanghai Maritime Univ Dept Elect Engn & Automat Shanghai 200135 Peoples R China

ISBN: (纸本)9781424467129

In this study, a two-level scheme with robust dynamic real-time optimization and distributed model predictive control (DMPC) is presented for plant-wide processes. On the top layer, chance-constrained programming (CCP) is employed in the real-time optimization with economic and model uncertainties, in which the constraints containing stochastic parameters are guaranteed to be satisfied at a high level of probability. On the lower layer, the on-line optimization of the whole system is decomposed into that of several small cooperative subsystems in distributed structures. The walking beam reheating furnace optimization and control problems are illustrated to verify the effectiveness and practicality of the proposed scheme.

关键词： plant-wide processes real-time optimization parametric uncertainty chance-constrained programming

来源：评论

学校读者我要写书评

暂无评论

Time-Cost Trade-off Problem with Fuzzy Random Parameters

Time-Cost Trade-off Problem with Fuzzy Random Parameters

引用

The First International Conference on Uncertainty Theory

作者： Hua Ke,Weimin Ma School of Economics and Management,Tongji University,Shanghai,200092,China

The time-cost trade-off problem studies how to modify project activities to achieve the trade-off between the completion time and the total project *** real world,the trade-off between the total project cost and the completion time,and the uncertainty of the external environment are both considerable for *** this paper,a new fuzzy random time-cost trade-off model is proposed,in which the philosophy of chance-constrained programming is introduced as decision-making *** approach by integrating fuzzy random simulation and genetic algorithm is produced to search the quasi-optimal *** the whole,this paper is to illustrate the process of achieving the optimal balance of the completion time and the project total cost in mixed uncertain environment with randomness and fuzziness.

关键词： Time-cost trade-off Fuzzy random simulation chance-constrained programming Genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

Planning of municipal solid waste management systems under dual uncertainties: a hybrid interval stochastic programming approach

引用

STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT 2009年第6期23卷 707-720页

作者： Cheng, G. H. Huang, G. H. Li, Y. P. Cao, M. F. Fan, Y. R. N China Elect Power Univ Chinese Res Acad Environm Sci Beijing *** Peoples R China N China Elect Power Univ Energy & Environm Res Ctr Beijing 102206 Peoples R China Peking Univ Coll Urban & Environm Sci Beijing 100871 Peoples R China

In this study, a random-boundary-interval linear programming (RBILP) method is developed and applied to the planning of municipal solid waste (MSW) management under dual uncertainties. In the RBILP model, uncertain inputs presented as interval numbers can be directly communicated into the optimization process;besides, intervals with uncertain lower and upper bounds can be handled through introducing the concept of random boundary interval. Consequently, robustness of the optimization process can be enhanced. To handle uncertainties with such complex presentations, an integrated chance-constrained programming and interval-parameter linear programming approach (ICCP) is proposed. ICCP can help analyze the reliability of satisfying (or risk of violating) system constraints under uncertainty. The applicability of the proposed RBILP and ICCP approach is validated through a case study of MSW management. Violations for capacity constraints are allowed under a range of significant levels. Interval solutions associated with different risk levels of constraint violation are obtained. They can be used for generating decision alternatives and thus helping waste managers to identify desired policies under various environmental, economic, and system-reliability constraints.

关键词： chance-constrained programming Inexact optimization Dual uncertainty Random boundary interval Solid waste management

来源：评论

学校读者我要写书评

暂无评论

Optimization models and a GA-based algorithm for stochastic time-cost trade-off problem

引用

APPLIED MATHEMATICS AND COMPUTATION 2009年第1期215卷 308-313页

作者： Ke, Hua Ma, Weimin Ni, Yaodong Tongji Univ Sch Econ & Management Shanghai 200092 Peoples R China

In real-life projects, both the trade-off between the project cost and the project completion time, and the uncertainty of the environment are considerable aspects for decision-makers. However, the research on the time-cost trade-off problem seldom concerns stochastic environments. Besides, optimizing the expected value of the objective is the exclusive decision-making criterion in the existing models for the stochastic time-cost trade-off problem. In this paper, two newly developed alternative stochastic time-cost trade-off models are proposed, in which the philosophies of chance-constrained programming and dependent-chance programming are adopted for decision-making. In addition, a hybrid intelligent algorithm integrating stochastic simulations and genetic algorithm is designed to search the quasi-optimal schedules under different decision-making criteria. The goal of the paper is to reveal how to obtain the optimal balance of the project completion time and the project cost in stochastic environments. (C) 2009 Elsevier Inc. All rights reserved.

关键词： Time-cost trade-off chance-constrained programming Dependent-chance programming Stochastic programming Genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

Product mix problems considering several probabilistic conditions and flexibility of constraints

引用

COMPUTERS & INDUSTRIAL ENGINEERING 2009年第3期56卷 918-936页

作者： Hasuike, Takashi Ishii, Hiroaki Osaka Univ Grad Sch Informat Sci & Technol Dept Informat & Phys Sci Suita Osaka 5650871 Japan

This paper considers product mix problems including randomness of future returns, ambiguity of coefficients and flexibility of upper value with respect to each constraint such as budget, human resource, time and several costs. Particularly, the flexibility is assumed to be a fuzzy goal. Then, several models based on maximizing total future profits under a level of satisfaction to each fuzzy goal are proposed. Furthermore, the model considering preference ranking to each fuzzy goal of constraints is proposed. Since these problems are basically formulated as nonlinear programming problems, the transformations into deterministic equivalent problems are introduced and the efficient solution methods are developed. A numerical example for product mix problem is given to illustrate our proposed models. (C) 2008 Elsevier Ltd. All rights reserved.

关键词： Product mix problems Multi-objective fuzzy programming chance-constrained programming Probability maximization model

来源：评论

学校读者我要写书评

暂无评论

A Decision-Analytic Approach to Reliability-Based Design Optimization

引用

OPERATIONS RESEARCH 2009年第5期57卷 1262-1270页

作者： Bordley, Robert F. Pollock, Stephen M. Gen Motors Tech Ctr Warren MI 48090 USA Univ Michigan Ann Arbor MI 48109 USA

Reliability-based design optimization is concerned with designing a product to optimize an objective function, given uncertainties about whether various design constraints will be satisfied. However, the widespread practice of formulating such problems as chance-constrained programs can lead to misleading solutions. While a decision-analytic approach would avoid this undesirable result, many engineers find it difficult to determine the utility functions required for a traditional decision analysis. This paper presents an alternative decision-analytic formulation that, although implicitly using utility functions, is more closely related to probability maximization formulations with which engineers are comfortable and skilled. This result combines the rigor of decision analysis with the convenience of existing optimization approaches.

关键词： chance-constrained programming decision analysis stochastic 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：