检索结果-内蒙古大学图书馆

Application of chance-constrained programming for stochastic group shop scheduling problem

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2009年第3-4期42卷 321-334页

作者： Ahmadizar, Fardin Ghazanfari, Mehdi Ghomi, Seyyed Mohammad Taghi Fatemi Iran Univ Sci & Technol Dept Ind Engn Tehran *** Iran Amirkabir Univ Technol Dept Ind Engn Tehran Iran

In this paper, we study a group shop scheduling (GSS) problem subject to uncertain release dates and processing times. The GSS problem is: a general formulation including the other shop scheduling problems such as the flow shop, the job shop, and the open shop scheduling problems. The objective is to find a job schedule which minimizes the total weighted completion time. We solve this problem based on the chance-constrained programming. First, the problem is fomulated in a form of stochastic programming and then prepared in a form of deterministic mixed binary integer linear programming such that it can be solved by a linear programming solver. To solve the problem efficiently, we develop an efficient hybrid method. Exploiting a heuristic algorithm in order to satisfy the constraints, an ant colony optimization algorithm is applied to construct high-quality solutions to the problem. The proposed approach is tested on instances where the random variables are normally, uniformly, or exponentially distributed.

关键词： Group shops scheduling Uncertain release dates and processing times Total weighted completion time chance-constrained programming Ant colony algorithm Heuristic algorithm

来源：评论

学校读者我要写书评

暂无评论

Design of close-loop supply chain network under uncertainty using hybrid genetic algorithm: A fuzzy and chance-constrained programming model

引用

COMPUTERS & INDUSTRIAL ENGINEERING 2015年 88卷 444-457页

作者： Dai, Zhuo Zheng, Xiaoting Jiu Jiang Univ Sch Elect Commerce Jiu Jiang City 332005 Jiangxi Peoples R China

The design of closed-loop supply chain network is one of the important issues in supply chain management. This research proposes a multi-period, multi-product, multi-echelon closed-loop supply chain network design model under uncertainty. Because of its complexity, a solution framework which integrates Monte Carlo simulation embedded hybrid genetic algorithm, fuzzy programming and chance-constrained programming jointly deal with the issue. A fuzzy programming and chance-constrained programming approach take up the uncertainty issue. Monte Carlo simulation embedded hybrid genetic algorithm is employed to determine the configuration of CLSC network. Parameters of GA are chosen to balance two aims. One aim is that the best value is global optimum, that is, maximum profit. The other aim is that the computational time is as short as possible. Non-parametric test confirms the advantage of hybrid GA. Then, the validity of Monte Carlo simulation embedded hybrid genetic algorithm is verified. The impacts of uncertainty in disposed rates, demands, and capacities on the overall profit of CLSC network are studied through sensitivity analysis. The proposed model is effective in designing CLSC network under uncertain environment. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Close-loop supply chain Network design Uncertainty Monte Carlo simulation embedded hybrid genetic algorithm Fuzzy programming chance-constrained programming

来源：评论

学校读者我要写书评

暂无评论

Managing Data Quality of the Data Warehouse: A chance-constrained programming Approach

引用

INFORMATION SYSTEMS FRONTIERS 2021年第2期23卷 375-389页

作者： Liu, Qi Feng, Gengzhong Tayi, Giri Kumar Tian, Jun Xi An Jiao Tong Univ Sch Management 28 Xianning Rd Xian 710049 Shaanxi Peoples R China Minist Educ Proc Control & Efficiency Engn Key Lab 28 Xianning Rd Xian 710049 Shaanxi Peoples R China SUNY Albany Sch Business Albany NY 12222 USA

To make informed decisions, managers establish data warehouses that integrate multiple data sources. However, the outcomes of the data warehouse-based decisions are not always satisfactory due to low data quality. Although many studies focused on data quality management, little effort has been made to explore effective data quality control strategies for the data warehouse. In this study, we propose a chance-constrained programming model that determines the optimal strategy for allocating the control resources to mitigate the data quality problems of the data warehouse. We develop a modified Artificial Bee Colony algorithm to solve the model. Our work contributes to the literature on evaluation of data quality problem propagation in data integration process and data quality control on the data sources that make up the data warehouse. We use a data warehouse in the healthcare organization to illustrate the model and the effectiveness of the algorithm.

关键词： Data quality Data warehouse chance-constrained programming Optimization model Artificial bee Colony algorithm

来源：评论

学校读者我要写书评

暂无评论

A NOVEL SEPARATE chance-constrained programming MODEL TO DESIGN A SUSTAINABLE MEDICAL VENTILATOR SUPPLY CHAIN NETWORK DURING THE COVID-19 PANDEMIC

引用

JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION 2023年第2期19卷 1395-1425页

作者： Abad, Amin Reza Kalantari Khalil Barzinpour, Farnaz Pasandideh, Seyed Hamid Reza Iran Univ Sci & Technol Dept Ind Engn Tehran Iran Kharazmi Univ Fac Engn Dept Ind Engn Tehran Iran

Providing new models or designing sustainable networks in recent studies represents a growing trend. However, there is still a gap in the simultaneous modeling of the three dimensions of sustainability in the electronic medical device supply chain (SC). In this paper, a novel hybrid chance-constrained programming and cost function model is presented for a green and sustainable closed-loop medical ventilator SC network design. To bring the problem closer to reality, a wide range of parameters including all cost parameters, demands, the upper bound of the released co2, and the minimum percentage of the units of product to be disposed and collected from a customer and to be dismantled and shipped from DCs are modeled as uncertain along with the normal probability distribution. The problem was first formulated into the framework of a bi-objective stochastic mixed-integer linear programming (MILP) model;then, it was reformulated into a tri-objective deterministic mixed-integer nonlinear programming (MINLP) one. In order to model the environmental sustainability dimension, in addition to handling the total greenhouse gas emissions, the total waste products were also controlled. The efficiency and applicability of the proposed model were tested in an Iranian medical ventilator production and distribution network. For sensitivity analyses, the effect of some critical parameters on the values of the objective functions was carefully examined. Finally, valuable managerial insights into the challenges of companies during the COVID-19 pandemic were presented. Numerical results showed that with the increase in the number of customers in the COVID-19 crisis, social responsibility could improve cost mean by up to 8%.

关键词： Healthcare system sustainable supply chain design closed-loop supply chain ventilator COVID-19 pandemic MINLP optimization chance-constrained programming multi-objective optimization goal attainment

来源：评论

学校读者我要写书评

暂无评论

Energy management for active distribution network incorporating office buildings based on chance-constrained programming

引用

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2022年 134卷 107360-107360页

作者： Su, Su Li, Zening Jin, Xiaolong Yamashita, Koji Xia, Mingchao Chen, Qifang Beijing Jiaotong Univ Natl Act Distribut Network Technol Res Ctr Beijing 100044 Peoples R China Tech Univ Denmark Ctr Elect Power & Energy Elektrovej 325 DK-2800 Lyngby Denmark Univ Calif Riverside Elect & Comp Engn Riverside CA 92521 USA

Aiming to the more flexible operation of the active distribution network (ADN), an energy management method for ADN incorporating office buildings is proposed based on chance-constrained programming. First, based on the thermal dynamics of buildings, an energy consumption prediction model of office buildings with integrated thermostatically controlled loads (TCLs) is developed. Then, an optimal energy management strategy for the ADN is proposed through the branch flow model (BFM) and the second-order cone relaxation (SOCR), considering the constraints of the grid and office buildings. The chance-constrained programming is exploited to consider further the uncertainties of photovoltaic (PV) power and ambient temperature, and the optimization model of the ADN incorporating office buildings is reformulated as a mixed-integer second-order cone programming (MISOCP) problem, using the deterministic transformation of chance constraints. Finally, the impact of the office buildings with TCLs on the economic operation of the ADN is analyzed under different confidence levels in the winter heating scenario. Numerical studies justify that the lower confidence level capitalizes on the thermal storage characteristics of office buildings retaining the temperature comfort of office workers to attain the flexible operation of the ADN additionally.

关键词： Active distribution network (ADN) chance-constrained programming Energy management Office buildings Thermostatically controlled loads (TCLs)

来源：评论

学校读者我要写书评

暂无评论

Stochastic congestion management considering power system uncertainties: a chance-constrained programming approach

引用

TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES 2016年第1期24卷 61-75页

作者： Hojjat, Mehrdad Javidi, Mohammad Hossein Yazdanpanah, Dariush Islamic Azad Univ Shahroud Branch Fac Elect & Comp Engn Shahrood Iran Ferdowsi Univ Mashhad Dept Elect Engn Mashhad Iran Khorasan Reg Elect Co Mashhad Iran

Considering system uncertainties in developing power systems, algorithms such as congestion management (CM) are vital in power system analysis and studies. This paper proposes a new model for power system CM by considering power system uncertainties based on chance-constrained programming (CCP). In the proposed approach, transmission constraints are taken into account by stochastic, instead of deterministic, models. The proposed approach considers network uncertainties with a specific level of probability in the optimization process, and then an analytical approach is used to solve the new model of stochastic congestion management. In this approach, the stochastic optimization problem is transformed into an equivalent deterministic problem. Moreover, an efficient numerical approach based on a real-coded genetic algorithm and Monte Carlo technique is proposed to solve the CCP-based congestion management problem in order to make a comparison to the analytical approach. The effectiveness of the proposed approach is evaluated by applying the method to the IEEE 30-bus test system. The results show that the proposed CCP model and the analytical solving approach outperform the existing models.

关键词： Congestion management system uncertainties chance-constrained programming Monte Carlo simulation stochastic optimization

来源：评论

学校读者我要写书评

暂无评论

Two-stage fuzzy chance-constrained programming: application to water resources management under dual uncertainties

引用

STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT 2009年第3期23卷 349-359页

作者： Guo, P. Huang, G. H. Univ Waterloo Dept Civil & Environm Engn Waterloo ON N2L 3G1 Canada Univ Regina Environm Syst Engn Program Regina SK S4S 0A2 Canada

In this study, a two-stage fuzzy chance-constrained programming (TFCCP) approach is developed for water resources management under dual uncertainties. The concept of distribution with fuzzy probability (DFP) is presented as an extended form for expressing uncertainties. It is expressed as dual uncertainties with both stochastic and fuzzy characteristics. As an improvement upon the conventional inexact linear programming for handling uncertainties in the objective function and constraints, TFCCP has advantages in uncertainty reflection and policy analysis, especially when the input parameters are provided as fuzzy sets, probability distributions and DFPs. TFCCP integrates the two-stage stochastic programming (TSP) and fuzzy chance-constrained programming within a general optimization framework. TFCCP incorporates the pre-regulated water resources management policies directly into its optimization process to analyze various policy scenarios;each scenario has different economic penalty when the promised amounts are not delivered. TFCCP is applied to a water resources management system with three users. Solutions from TFCCP provide desired water allocation patterns, which maximize both the system's benefits and feasibility. The results indicate that reasonable solutions were generated for objective function values and decision variables, thus a number of decision alternatives can be generated under different levels of stream flows, alpha-cut levels and fuzzy dominance indices.

关键词： chance-constrained programming Decision making Fuzzy Uncertainty Water resources

来源：评论

学校读者我要写书评

暂无评论

Distributional Assumptions in chance-constrained programming Models of Stochastic Water Pollution

引用

ENVIRONMENTAL MODELING & ASSESSMENT 2010年第4期15卷 273-281页

作者： Kataria, Mitesh Elofsson, Katarina Hasler, Berit Max Planck Inst Econ Strateg Interact Grp D-07745 Jena Germany Swedish Univ Agr Sci Dept Econ S-75007 Uppsala Sweden Aarhus Univ Natl Environm Res Inst DK-4000 Roskilde Denmark

In the water management literature both the normal and log-normal distribution are commonly used to model stochastic water pollution. The normality assumption is usually motivated by the central limit theorem, while the log-normality assumption is often motivated by the need to avoid the possibility of negative pollution loads. We utilize the truncated normal distribution as an alternative to these distributions. Using probabilistic constraints in a cost-minimization model for the Baltic Sea, we show that the distribution assumption bias is between 1% and 60%. Simulations show that a greater difference is to be expected for data with a higher degree of truncation. Using the normal distribution instead of the truncated normal distribution leads to an underestimation of the true cost. On the contrary, the difference in cost when using the normal versus the log-normal can be positive as well as negative.

关键词： Cost effectiveness Water pollution chance-constrained programming Log-normal distribution Truncated normal distribution

来源：评论

学校读者我要写书评

暂无评论

Dynamic Economic Dispatch for Microgrid Based on the chance-constrained programming

引用

JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY 2017年第3期12卷 1064-1072页

作者： Huang, Daizheng Xie, Lingling Wu, Zhihui Guangxi Med Univ Dept Biomed Engn Nanning Peoples R China Guangxi Univ Sch Elect Engn Nanning Peoples R China

The power of controlled generators in microgrids randomly fluctuate because of the stochastic volatility of the outputs of photovoltaic systems and wind turbines as well as the load demands. To address and dispatch these stochastic factors for daily operations, a dynamic economic dispatch model with the goal of minimizing the generation cost is established via chance-constrained programming. A Monte Carlo simulation combined with particle swarm optimization algorithm is employed to optimize the model. The simulation results show that both the objective function and constraint condition have been tightened and that the operation costs have increased. A higher stability of the system corresponds to the higher operation costs of controlled generators. These operation costs also increase along with the confidence levels for the objective function and constraints.

关键词： Microgrid Dynamic economic dispatch chance-constrained programming

来源：评论

学校读者我要写书评

暂无评论

An inexact inventory-theory-based chance-constrained programming model for solid waste management

引用

STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT 2014年第8期28卷 1939-1955页

作者： Chen, XiuJuan Huang, GuoHe Suo, MeiQin Zhu, Hua Dong, Cong Univ Regina Environm Syst Engn Program Fac Engn & Appl Sci Regina SK S4S 0A2 Canada Hebei Univ Engn Sch Urban Construct Handan 056038 Hebei Peoples R China North China Elect Power Univ SC Energy & Environm Res Acad Beijing 102206 Peoples R China Univ Regina Inst Energy Environm & Sustainable Communities Regina SK S4S 0A2 Canada North China Elect Power Univ Resources & Environm Res Acad MOE Key Lab Reg Energy & Environm Syst Optimizat Beijing 102206 Peoples R China

In this study, an inexact inventory-theory-based chance-constrained programming (IICP) model is proposed for planning waste management systems. The IICP model is derived through introducing inventory theory model into a general inexact chance-constrained programming framework. It can not only tackle uncertainties presented as both probability distributions and discrete intervals, but also reflect the influence of inventory problem in decision-making problems. The developed method is applied to a case study of long-term municipal solid waste (MSW) management planning. Solutions of total waste allocation, waste allocation batch and waste transferring period associated different risk levels of constraint violation are obtained. The results can be used to identify inventory-based MSW management planning with minimum system cost under various constraint-violation risks. Compared with the ICP model, the developed IICP model can more actually reflect the complexity of MSW management systems and provide more useful information for decision makers.

关键词： Inventory Uncertainty Interval chance-constrained programming Waste management

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：