检索结果-内蒙古大学图书馆

An integrated supply chain model for new products with imprecise production and supply under scenario dependent fuzzy random demand

引用

INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 2014年第5期45卷 873-887页

作者： Nagar, Lokesh Dutta, Pankaj Jain, Karuna Indian Inst Technol Shailesh J Mehta Sch Management Bombay 400076 Maharashtra India

In the present day business scenario, instant changes in market demand, different source of materials and manufacturing technologies force many companies to change their supply chain planning in order to tackle the real-world uncertainty. The purpose of this paper is to develop a multi-objective two-stage stochastic programming supply chain model that incorporates imprecise production rate and supplier capacity under scenario dependent fuzzy random demand associated with new product supply chains. The objectives are to maximise the supply chain profit, achieve desired service level and minimise financial risk. The proposed model allows simultaneous determination of optimum supply chain design, procurement and production quantities across the different plants, and trade-offs between inventory and transportation modes for both inbound and outbound logistics. Analogous to chance constraints, we have used the possibility measure to quantify the demand uncertainties and the model is solved using fuzzy linear programming approach. An illustration is presented to demonstrate the effectiveness of the proposed model. Sensitivity analysis is performed for maximisation of the supply chain profit with respect to different confidence level of service, risk and possibility measure. It is found that when one considers the service level and risk as robustness measure the variability in profit reduces.

关键词： supply chain management new products two-stage stochastic programming fuzzy random demand possibility measure

来源：评论

学校读者我要写书评

暂无评论

Reverse logistics network design and planning utilizing conditional value at risk

引用

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2014年第2期237卷 487-497页

作者： Soleimani, Hamed Govindan, Kannan IAU Qazvin Branch Fac Ind & Mech Engn Qazvin Iran Univ Southern Denmark Dept Econ & Business Odense M Denmark

Nowadays, due to some social, legal, and economical reasons, dealing with reverse supply chain is an unavoidable issue in many industries. Besides, regarding real-world volatile parameters, lead us to use stochastic optimization techniques. In location-allocation type of problems (such as the presented design and planning one), two-stage stochastic optimization techniques are the most appropriate and popular approaches. Nevertheless, traditional two-stage stochastic programming is risk neutral, which considers the expectation of random variables in its objective function. In this paper, a risk-averse two-stage stochastic programming approach is considered in order to design and planning a reverse supply chain network. We specify the conditional value at risk (CVaR) as a risk evaluator, which is a linear, convex, and mathematically well-behaved type of risk measure. We first consider return amounts and prices of second products as two stochastic parameters. Then, the optimum point is achieved in a two-stage stochastic structure regarding a mean-risk (mean-CVaR) objective function. Appropriate numerical examples are designed, and solved in order to compare the classical versus the proposed approach. We comprehensively discuss about the effectiveness of incorporating a risk measure in a two-stage stochastic model. The results prove the capabilities and acceptability of the developed risk-averse approach and the affects of risk parameters in the model behavior. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Conditional value at risk Design and planning End of life products Reverse supply chain two-stage stochastic programming

来源：评论

学校读者我要写书评

暂无评论

Simulation- Based Inexact two- stage Chance- Constraint Quadratic programming for Sustainable Water Quality Management under Dual Uncertainties

引用

JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT 2014年第3期140卷 298-312页

作者： Li, Ting Li, Pu Chen, Bing Hu, Ming Zhang, Xiaofei North China Elect Power Univ Resources & Environm Res Acad Key Lab Reg Energy & Environm Syst Optimizat Minist Educ Beijing 102206 Peoples R China Mem Univ Newfoundland Fac Engn & Appl Sci Northern Reg Persistent Organ Pollut Control Lab St John NF A1B 3X5 Canada

Water quality planning is complicated itself but further challenged by the existence of uncertainties and nonlinearities in terms of model formulation and solution. In this study, a simulation-based inexact two-stage chance-constraint quadratic programming (SITCQP) approach was developed for water quality management. The SITCQP model was a hybrid of two-stage stochastic programming (TSP), chance-constraint programming (CCP), inexact quadratic programming (IQP), and multisegment stream water quality simulation. A water quality simulation model was provided for reflecting the relationship between the pollution-control actions before wastewater discharge and the environmental responses after the discharge. Interval quadratic polynomials were employed to reflect the uncertainties and nonlinearities associated with the costs for wastewater treatment. Uncertainties derived from water quality standards were characterized as random variables with normal distributions. The proposed approach was applied to a hypothetical case in water quality management. The modeling solutions were presented as combinations of deterministic, interval and distributional information, which could facilitate predictions for different forms of uncertainties. The results were valuable for helping decision makers generate alternatives between wastewater treatment and stream water quality management.

关键词： Computer programming stochastic processes Water quality Uncertainty principles Oxygen demand Sustainable development Simulation Inexact quadratic programming two-stage stochastic programming Chance constraint programming Water quality Uncertainty Biochemical oxygen demand

来源：评论

学校读者我要写书评

暂无评论

A two-stage stochastic transportation problem with fixed handling costs and a priori selection of the distribution channels

引用

TOP 2014年第3期22卷 1123-1147页

作者： Hinojosa, Yolanda Puerto, Justo Saldanha-da-Gama, Francisco Univ Seville Dept Econ Aplicada 1 Seville Spain Univ Seville Fac Matemat Dept Estadist & Invest Operat Seville Spain Univ Lisbon Fac Ciencias DEIO CIO Lisbon Portugal

In this paper, a transportation problem comprising stochastic demands, fixed handling costs at the origins, and fixed costs associated with the links is addressed. It is assumed that uncertainty is adequately captured via a finite set of scenarios. The problem is formulated as a two-stage stochastic program. The goal is to minimize the total cost associated with the selected links plus the expected transportation and fixed handling costs. A prototype problem is initially presented which is then progressively extended to accommodate capacities at the origins and multiple commodities. The results of an extensive set of computational tests are reported and discussed.

关键词： Transportation stochastic demands Fixed handling costs two-stage stochastic programming

来源：评论

学校读者我要写书评

暂无评论

Considering The Load Uncertainty For Solving Security Constrained Unit Commitment Problem In Presence of Plug-In Electric Vehicle 22

Considering The Load Uncertainty For Solving Security Constr...

引用

22nd Iranian Conference on Electrical Engineering (ICEE)

作者： Imani, S. M. Hossein Asghari, S. Ameli, M. T. Univ Guilan Dept Elect Engn Rasht Iran Shahid Beheshti Univ Dept Elect Engn Tehran Iran

ISBN: (纸本)9781479944095

In this paper, the load uncertainty for solving Security constrained unit commitment (SCUC) problem in presence of plug-in electric vehicle is studied. SCUC is one of the most important research areas in power systems which enables commitment scheduling table of the generation unit commitment in order to maximize the security and minimize the cost, beside satisfaction of the constraints of the system and units, during a specified time period. Recent advances in technology, caused power system operators to focus more on renewable energy resources beside thermal units. Vehicle to grid (V2G) technology is one of these new resources of energy. On this aim, V2G by reducing the dependence of the power generation system to small and expensive thermal units, can play an important role in reducing operation cost and load fluctuation management. According to the probability of error existence in load forecasting, the system planner must appoint the generation pattern in a way that beside of load satisfaction, the reserves been provided and the error of load forecasting been compensated. In this paper, by - stochastic programming, the uncertainty of load forecasting while solving SCUC problem in a short period (24 hours) is investigated. Nowadays one of the most effective strategies for evaluating the influences of V2G connection in an efficient operation of generation system, is SCUC performing on the power systems in which V2Gs are connected to it in different buses. Therefore, this issue is considered in this paper, in a way that results of numerical studies on independence presence of V2G, and the improvement of operation indices are illustrated.

关键词： Security Constrained Unit Commitment (SCUC) two-stage stochastic programming Uncertainty in Load Forecasting Vehicle To Grid Technology (V2G)

来源：评论

学校读者我要写书评

暂无评论

two-stage stochastic programming with fixed recourse via scenario planning with economic and operational risk management for petroleum refinery planning under uncertainty

引用

CHEMICAL ENGINEERING AND PROCESSING-PROCESS INTENSIFICATION 2008年第9-10期47卷 1744-1764页

作者： Khor, Cheng Seong Elkamel, Ali Ponnambalam, Kumaraswamy Douglas, Peter L. Univ Waterloo Dept Chem Engn Waterloo ON N2L 3G1 Canada Univ Waterloo Dept Syst Design Engn Waterloo ON N2L 3G1 Canada Univ Teknol PETRONAS Chem Engn Programme Tronoh Malaysia

This work proposes a hybrid of stochastic programming (SP) approaches for an optimal midterm refinery planning that addresses three sources of uncertainties: prices of crude oil and saleable products, demands, and yields. An SP technique that utilizes compensating slack variables is employed to explicitly account for constraints' violations to increase model tractability. Four approaches are considered to ensure solution and model robustness: (1) the Markowitz's mean-variance (MV) model to handle randomness in the objective function coefficients by minimizing the variance (economic risk) of the expected value of the random coefficients;(2): the two-stage SP with fixed recourse approach to deal with randomness in the RHS and LHS coefficients of the constraints by minimizing the expected recourse costs due to constraints' violations;(3) incorporation of the MV model within the framework developed in (2) to formulate a mean-risk model that minimizes both the expectation and the operational risk measure of variance of the recourse costs;and (4) reformulation of the model in (3) by adopting mean-absolute deviation (MAD) as the measure of operational risk imposed by the recourse costs for a novel refinery planning application. A representative numerical example is illustrated. (c) 2007 Elsevier B. V. All rights reserved.

关键词： two-stage stochastic programming refinery planning optimization under uncertainty scenario analysis mean-variance mean-absolute deviation (MAD)

来源：评论

学校读者我要写书评

暂无评论

Fuzzy two-stage non-point source pollution management model for agricultural systems-A case study for the Lake Tai Basin, China

引用

AGRICULTURAL WATER MANAGEMENT 2013年 121卷 27-41页

作者： Liu, M. Huang, G. H. Liao, R. F. Li, Y. P. Xie, Y. L. North China Elect Power Univ Resources & Environm Res Acad MOE Key Lab Reg Energy & Environm Syst Optimizat Beijing 102206 Peoples R China Univ Regina Fac Engn & Appl Sci Environm Syst Engn Program Regina SK S4S 0A2 Canada

Non-point source (NPS) pollution from agricultural lands has aroused widespread concerns throughout the world. In this study, an interval fuzzy two-stage stochastic non-point source pollution mitigation (IFTNS) model was developed for agricultural systems management under uncertainty through land retirement and nutrients discharge trading programs. The developed IFTNS model incorporated fuzzy possibilistic programming (FPP) and interval linear programming (ILP) within a general two-stage stochastic programming (TSP) framework. The IFTNS model could not only deal with uncertainties presented as probability density functions, fuzzy membership functions, and discrete interval numbers, but also provide an effective linkage between the pre-regulated agricultural systems management policies and the associated economic implications. Moreover, the IFTNS model could help to analyze various trading scenarios associated with different plausibility degree levels. The IFTNS model was applied to a case study with a nutrients discharge trading program within a subcatchment of the Lake Tai Basin in China. The results indicated that reasonable solutions under different plausibility degree levels were generated, which could be used for generating decision alternatives and thus help decision makers to identify desired agricultural NPS pollution mitigation policies. The results also indicated that land retirement and nutrients discharge trading programs could effectively achieve agricultural NPS pollution mitigation and maximize net system benefits. (c) 2013 Elsevier B.V. All rights reserved.

关键词： Agricultural non-point source pollution Land retirement Nutrients discharge trading two-stage stochastic programming Fuzzy possibilistic programming Interval linear programming

来源：评论

学校读者我要写书评

暂无评论

A bi-objective stochastic optimization model for reliable warehouse network redesign

引用

MATHEMATICAL AND COMPUTER MODELLING 2013年第11-12期58卷 1804-1813页

作者： Razmi, Jafar Zahedi-Anaraki, AmirHossien Zakerinia, MohammadSaleh Univ Tehran Dept Ind Engn Tehran Iran Univ Calif Davis Inst Transportat Studies Davis CA 95616 USA

This paper proposes a developed bi-objective two-stage stochastic mixed-integer linear programming model for redesigning a reliable warehouse network. In this model, the warehouses capacity which should be phased out, remained, or relocated to other warehouses, and the shipment quantity of the product between the network nodes with a consideration for two delivery lead times is to be determined. Unlike most previous works, considering two delivery lead times, the maximum capacity for each warehouse location, reliability and uncertainty are taken into account in this study. The proposed bi-objective model includes: (1) minimizing average costs including the sum of fixed, production, transportation, relocation and capacity extension costs;(2) maximizing the coverage percentage of customer demand delivered within the preferred delivery lead time. In order to obtain Pareto optimal solutions, a novel version of epsilon-constraint method (i.e., the augmented epsilon-constraint) is applied. A real industrial case is applied to validate and verify the developed warehouse redesigning network model under reliability concept. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Supply chain network redesign two-stage stochastic programming Bi-objective optimization Augmented epsilon-constraint method

来源：评论

学校读者我要写书评

暂无评论

An interval-parameter two-stage stochastic fuzzy program with type-2 membership functions: an application to water resources management

引用

stochastic ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT 2013年第6期27卷 1493-1506页

作者： Wang, S. Huang, G. H. Univ Regina Fac Engn & Appl Sci Regina SK S4S 0A2 Canada Univ Regina Inst Energy Environm & Sustainable Communities Regina SK S4S 0A2 Canada

This paper presents an interval-parameter two-stage stochastic fuzzy programming with type-2 membership functions (ITSFP-T2MF) approach for supporting water resources management under uncertainty. ITSFP-T2MF is capable not only of dealing with a variety of uncertainties expressed as probability distributions, intervals, and type-2 fuzzy sets, but also of reflecting the complexity of uncertainty presented as the concept of a flexible fuzzy decision. A scenario-based solution method is proposed for solving ITSFP-T2MF, which takes into account different attitudes of decision makers (DMs) towards the objective-function value and constraints. Moreover, the solution method can ensure that no infeasible solutions are included in the results by means of a feasibility test and a constricting algorithm, leading to an enhanced system safety. ITSFP-T2MF is applied to a case study of water resources allocation under uncertainty. The results indicate that interval solutions can be obtained under different scenarios, which enhances the diversity of solutions for supporting the decisions of water resources allocation. Furthermore, a variety of decision alternatives can be generated under different policies for water resources management, which permits an in-depth policy analysis associated with different levels of economic penalties when the promised water-allocation targets are violated, and thus helps DMs identify desired water-allocation plans according to practical situations.

关键词： Decision-making Interval two-stage stochastic programming Type-2 fuzzy set Uncertainty Water resources management

来源：评论

学校读者我要写书评

暂无评论

A hybrid waste-flow allocation model considering multiple stage and interval-fuzzy chance constraints

引用

CIVIL ENGINEERING AND ENVIRONMENTAL SYSTEMS 2012年第1期29卷 59-78页

作者： Xu, Y. Huang, G. H. Cao, M. F. Dong, C. Li, Y. F. N China Elect Power Univ MOE Key Lab Reg Energy & Environm Syst Optimizat Resources & Environm Res Acad Beijing 102206 Peoples R China

An inexact two-stage fuzzy chance-constrained programming (ITSFCCP) model was developed in this study for dealing with multiple uncertainties associated with solid waste management systems. The model was formulated by incorporating fuzzy chance-constrained programming and interval linear programming within a two-stage stochastic programming framework. The model could be used to facilitate analysis of the policy scenarios;meanwhile, the uncertainties associated with solid waste management systems could be expressed as probability distributions, possibility distribution and discrete intervals. A long-term waste planning problem was used to demonstrate the applicability of the ITSFCCP model. The study results indicated that ITSFCCP could provide a linkage to pre-defined policies and allowed violation of system constraints at predefined confidence levels. Moreover, it allowed uncertain information presented as discrete intervals to be communicated into the optimisation process. ITSFCCP could help waste managers to identify desired policies and gain insights into the tradeoffs between system economy and reliability.

关键词： fuzzy chance-constrained programming interval linear programming two-stage stochastic programming solid waste management uncertainty

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：