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General asymptotic and submodular results for the Median Problem with Unreliable Facilities

OPERATIONS RESEARCH LETTERS 2015年第5期43卷 519-521页

作者： Gueye, Serigne Menezes, Mozart B. C. Univ Avignon & Pays Vaucluse LIA F-84911 Avignon 9 France KEDGE Business Sch F-33405 Talence France

The Median Problem with Unreliable Facilities (MPUF) consists of locating facilities such that the expected cost of serving the customers, considering possibility of failure, is minimized. We consider a general version of MPUF where facility disruptions may have non-zero correlation while the current approaches assume independence. We express the problem as a two-stage stochastic program and show that, independently of correlation values, some previous asymptotic and submodular results remain valid. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Facility location Disruptions two-stage stochastic programming

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A Model to Incorporate Demand Response Programs in Security Constrained Unit Commitment 5

A Model to Incorporate Demand Response Programs in Security ...

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2015 International Conference on Industrial Engineering and Operations Management (IEOM)

作者： Olamaei, Javad Khademi, Mohammad Mehdi Arjomand, Abdolsaheb Islamic Azad Univ Dept Elect Engn Fac Engn South Tehran Branch Tehran Iran Hormozgan Elect Power Distribut Co Hormozgan Iran

ISBN: (纸本)9781479960651

The ISO implements Security Constraint Unit Commitment (SCUC) for clearing of day-ahead market. In this paper, SCUC is also used for simultaneous clearing of energy and reserve market. Spinning reserve and of generating units and Demand Response Programs (DRPs) are considered as system operating reserves in the proposed model. A Mixed Integer programming model is proposed for power system modeling along with DRPs. The proposed model is applied to the IEEE RTS to demonstrate its effectiveness. The results show that the use of DRPs' reserve, reduce the system operation costs and have high impact in reliability improvement and reduction in market clearing price in critical or peak hours.

关键词： Simultaneous energy and reserve market Demand Response Programs (DRPs) security constraint unit commitment (SCUC) two-stage stochastic programming Expected energy not surved (EENS)

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Inexact rough-interval two-stage stochastic programming for conjunctive water allocation problems

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JOURNAL OF ENVIRONMENTAL MANAGEMENT 2009年第1期91卷 261-269页

作者： Lu, Hongwei Huang, Guohe He, Li Univ Regina EVSE Fac Engn & Appl Sci Regina SK S4S 0A2 Canada Peking Univ Coll Urban Environm Sci Beijing 100871 Peoples R China Ryerson Univ Dept Civil Engn Toronto ON M5B 2K3 Canada

An inexact rough-interval two-stage stochastic programming (IRTSP) method is developed for conjunctive water allocation problems. Rough intervals (RIs), as a particular case of rough sets, are introduced into the modeling framework to tackle dual-layer information provided by decision makers. Through embeding upper and lower approximation intervals, rough intervals are capable of reflecting complex parameters with the most reliable and possible variation ranges being identified. An interactive solution method is also derived. A conjunctive water-allocation system is then structured for characterizing the proposed model. Solutions indicate a detailed optimal allocation scheme with a rough-interval form;a total of [[1048.83, 2078.29]:[1482.26, 2020.60]] would be obtained under the pre-regulated inputs. Comparisons of the proposed model to a conventional and an interval two-stage stochastic programming model are also conducted. The results indicate that the optimal objective function values of TSP and ITSP always fall into the range of f(opt)(+/-(UAI)), while they are sometimes out of the range of f(opt)(+/-(LAI));the optimal solutions of decision variables also present this feature. This implies the reliability of IRTSP in handling conjunctive water allocation problems. (C) 2009 Elsevier Ltd. All rights reserved.

关键词： Rough intervals Conjunctive use Water resources management Uncertainty Inexact Agricultural irrigation two-stage stochastic programming

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NONLINEAR MIXED INTEGER programming MODELS AND ALGORITHMS FOR FAIR AND EFFICIENT LARGE SCALE EVACUATION PLANNING

NONLINEAR MIXED INTEGER PROGRAMMING MODELS AND ALGORITHMS FO...

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作者： Vedat Bayram Bilkent University

学位级别：博士

Shelters are safe facilities that protect a population from possible damaging effects of a disaster. Traffic management during an evacuation and the decision of where to locate the shelters are of critical importance to the performance of an evacuation plan. From the evacuation management authority's point of view, the desirable goal is to minimize the total evacuation time by computing a system optimum (SO). However, evacuees may not be willing to take long routes enforced on them by a SO solution; but they may consent to taking routes with lengths not longer than the shortest path to the nearest shelter site by more than a tolerable factor. We develop a model that optimally locates shelters and assigns evacuees to the nearest shelter sites by assigning them to shortest paths, shortest and nearest with a given degree of tolerance, so that the total evacuation time is minimized. As the travel time on a road segment is often modeled as a nonlinear function of the flow on the segment, the resulting model is a nonlinear mixed integer programming model. We develop a solution method that can handle practical size problems using second order cone programming techniques. Using our model, we investigate the trade-off between efficiency and fairness. Disasters are uncertain events. Related studies and real-life practices show that a significant uncertainty regarding the evacuation demand and the impact of the disaster on the infrastructure exists. The second model we propose is a scenario-based two-stage stochastic evacuation planning model that optimally locates shelter sites and that assigns evacuees to shelters and paths to minimize the expected total evacuation time, under uncertainty. The model considers the uncertainty in the evacuation demand and the disruption in the road network and shelter sites. We present a case study for an impending earthquake in Istanbul, Turkey. We compare the performance of the stochastic programming solutions to solutions based on single sc

关键词： Disaster Management Evacuation Traffic Management Shelter Location System Optimal Constrained System Optimal User Equilibrium Nearest Allocation two-stage stochastic programming Second Order Cone programming Benders Decomposition Pareto-optimal Cuts

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A bi-objective stochastic programming model for a centralized green supply chain with deteriorating products

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2014年 150卷 140-154页

作者： Sazvar, Z. Al-e-hashem, S. M. J. Mirzapour Baboli, A. Jokar, M. R. Akbari Inst Natl Sci Appl DISP Lab F-69621 Villeurbanne France ESC Rennes Sch Business F-35065 Rennes France Sharif Univ Technol Dept Ind Engn Tehran Iran

In recent years consumers and legislation have been pushing companies to design their activities in such a way as to reduce negative environmental impacts more and more. It is therefore important to examine the optimization of total supply chain costs and environmental impacts together. However, because of the recycling of deteriorated items, the environmental impacts of deteriorating items are more significant than those of non-deteriorating ones. The objective of this paper is to develop a stochastic mathematical model and to propose a new replenishment policy in a centralized supply chain for deteriorating items. In this model, we consider inventory and transportation costs, as well as the environmental impacts under uncertain demand. Several transportation vehicles producing various greenhouse gas (GHG) levels are considered. The best transportation vehicles and inventory policy are determined by finding a balance between financial and environmental criteria. In this way, we develop a linear mathematical model and present a numerical example from the real world to demonstrate its applicability and effectiveness. We then perform a sensitivity analysis and provide some managerial insights. Finally, more promising directions are suggested for future research. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Green supply chain two-stage stochastic programming Deteriorating products Transportation Uncertain demand

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A two-stage Multi-Criterion stochastic programming Model for Medical Supply Location in Biochemical Attacks

A Two-Stage Multi-Criterion Stochastic Programming Model for...

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9th International Conference on Natural Computation (ICNC)

作者： Zhu, Gaosong Yu, Hua Chinese Acad Sci Grad Univ Coll Engn & Informat Technol Beijing Peoples R China

ISBN: (纸本)9781467347143

We propose a stochastic optimization approach for the location and distribution problem of medical supplies to be used in Biochemical attacks. We develop a robust decision support mechanism. It is serviceable under the wide variety of possible disaster types and magnitudes. We develop a two-stage multi-criteria stochastic programming model in preparation for biochemical attacks. It is used to select the storage locations of medical supplies and required inventory levels for each type of medical supplies. Our model captures the attack specific information and possible effects of disasters through the use of disaster scenarios. Thus, we balance the preparedness and risk despite the uncertainties of biochemical attacks. We present a case study of our models based on sarin gas attack scenarios in the Beijing area.

关键词： biochemical attacks facility location medical supply two-stage stochastic programming

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Inexact Probabilistic Optimization Model and Its Application to Flood Diversion Planning in a Dynamic and Uncertain Environment

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JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT 2015年第8期141卷 04014093-04014093页

作者： Wang, S. Huang, G. H. Zhou, Y. Univ Regina Fac Engn & Appl Sci Regina SK S4S 0A2 Canada

Flood management systems involve a variety of complexities, such as multiple uncertainties and their interdependences, as well as multiregion and dynamic features. This paper thus presents an inexact two-stage mixed-integer programming with random coefficients (ITMP-RC) model for flood management in a dynamic and uncertain environment. ITMP-RC is capable of addressing dual uncertainties expressed as random boundary intervals that exist in the coefficients of the objective function. A case study of flood diversion planning is used to demonstrate the applicability of the proposed methodology. Results indicate that total system costs would be rising gradually with increased probabilities of occurrence, implying a trade-off between economic objective and system safety. A variety of decision alternatives can be obtained under different policy scenarios, which are useful for decision makers to formulate appropriate flood management policies according to practical situations. The performance of ITMP-RC is analyzed and compared with an inexact two-stage stochastic programming model. (C) 2014 American Society of Civil Engineers.

关键词： Dual uncertainties Flood diversion planning Fractile criterion optimization Random boundary intervals two-stage stochastic programming

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two-stage Chance-Constrained Fractional programming for Sustainable Water Quality Management under Uncertainty

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JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT 2015年第5期141卷 04014074-04014074页

作者： Zhou, X. Huang, G. H. Zhu, H. Yan, B. Univ Regina Inst Energy Environm & Sustainable Communities Regina SK S4S 0A2 Canada North China Elect Power Univ SC Energy & Environm Res Acad Beijing 102206 Peoples R China Xiamen Univ Technol Dept Environm Engn Xiamen 361024 Peoples R China

In this study, a two-stage chance-constrained fractional programming (TCFP) method is developed for dealing with water quality management problems associated with stochastic inputs. two-stage chance-constrained fractional programming is a hybrid of stochastic linear fractional programming (SLFP) and two-stage stochastic programming (TSP) methods. It can not only balance objectives of two aspects through converting a bi-objective problem into a ratio one but can also analyze various policy scenarios when the promised production targets are violated. For demonstrating its advantages, the proposed TCFP method is applied to a case study of water quality management where managers have to consider conflicting objectives between economic development and environmental conservation, as well as stochastic features expressed as probability distributions. The obtained solutions under different significance levels can help managers to identify desired policies under various environmental, economic, and constraint-violation conditions.

关键词： two-stage stochastic programming Linear fractional programming Chance-constrained programming Uncertainty Water quality management

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two-stage stochastic approach for spinning reserve allocation in dynamic economic dispatch

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Journal of Central South University 2014年第2期21卷 577-586页

作者：杨明张利韩学山程凤璐 Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education (Shandong University)

A novel approach was proposed to allocate spinning reserve for dynamic economic *** proposed approach set up a two-stage stochastic programming model to allocate *** model was solved using a decomposed algorithm based on Benders' *** model and the algorithm were applied to a simple 3-node system and an actual 445-node system for verification,*** results show that the model can save 84.5 US $ cost for the testing three-node system,and the algorithm can solve the model for 445-node system within 5 *** test results also illustrate that the proposed approach is efficient and suitable for large system calculation.

关键词： power system dynamic economic dispatch spinning reserve response risk two-stage stochastic programming Benders＇ decomposition

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Incorporating risk measures in closed-loop supply chain network design

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2014年第6期52卷 1843-1867页

作者： Soleimani, Hamed Seyyed-Esfahani, Mirmehdi Kannan, Govindan Amirkabir Univ Technol Dept Ind Engn & Management Syst Tehran Polytech Tehran Iran Univ Southern Denmark Dept Business & Econ Odense Denmark

This paper considers a location-allocation problem in a closed-loop supply chain (CLSC) with two extensions: first, demand and prices of new and return products are regarded as non-deterministic parameters and second, the objective function is developed from expected profit to three types of mean-risk ones. Indeed, design and planning an integrated CLSC in real-world volatile markets is an important and necessary issue. Further, risk-neutral approaches, which are considered expected values, are not efficient for such uncertain conditions. Hence, this paper, copes with the design and planning problem of a CLSC in a two-stage stochastic structure. Besides, risk criteria are considered through using three types of popular and well-behaved risk measures: mean absolute deviation, value at risk and conditional value at risk (CVaR). Consequently, three types of mean-risk models are developed as objective functions and decision-making procedures are undertaken based on the expected values and risk adversity criteria. Finally, performances of the developed mean-risk models are evaluated in various aspects. Results reveal that the inefficiencies of risk-neutral approaches can be overcome. In addition, in terms of quality of solutions, the acceptability of CVaR is proved when it is compared to other risk measures.

关键词： closed-loop supply chain design and planning two-stage stochastic programming conditional value at risk value at risk mean absolute deviation

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