检索结果-内蒙古大学图书馆

modelling a resilient yard template under storage demand fluctuations in a container terminal

ENGINEERING OPTIMIZATION 2019年第9期51卷 1547-1566页

作者： He, Junliang Tan, Caimao Shanghai Maritime Univ China Inst FTZ Supply Chain Shanghai Peoples R China Shanghai Maritime Univ Engn Res Ctr Container Supply Chain Technol Minist Educ Shanghai Peoples R China

This article investigates the generation of a resilient yard template, which has the property of resilience under storage demand fluctuations. A stochastic programming model is formulated aiming at minimizing the risk of containers without available storage slots being assigned in the designated area. Furthermore, a corresponding particle swarm optimization algorithm is proposed for solving the model. Finally, numerical experiments are conducted to verify the effectiveness of the proposed model and solution approaches.

关键词： Container terminal resilient yard template storage demand fluctuation stochastic programming model

来源：评论

学校读者我要写书评

暂无评论

An optimization model for economic feasibility analysis and design of decentralized waste-to-energy systems

引用

ENERGY 2016年 101卷 239-251页

作者： Xiong, Jie Ng, Tsan Sheng Adam Wang, Shuming Natl Univ Singapore Dept Ind & Syst Engn Block E1A1 Engn Dr 2 Singapore 117576 Singapore Univ Chinese Acad Sci Sch Econ & Management 80 Zhongguancun East Beijing 100190 Peoples R China CREATE Programme Natl Res Fdn NRF Singapore Prime Ministers Off CREATE Tower 15-021 Create Way Singapore 138602 Singapore

This paper considers a methodology for economic feasibility analysis of a decentralized hybrid WTE (waste-to-energy) system, when input waste streams and technical parameters can be uncertain. A hybrid WTE system is decentralized when there are possibly different owners of the waste treatment units. A two-stage stochastic programming model is proposed to evaluate and optimize the joint probability that each installed unit is able to achieve its own financial target, while adhering to stipulated environmental requirements. A case study is performed based on the city state of Singapore. The results show that, the proposed model can help provide the effective decision support for policy-makers in evaluating the appropriate technological mix of WTE alternatives. Furthermore, the designs generated by the proposed model can significantly improve the economic feasibility of the overall system without sacrificing certain installed unit's financial position. Finally, the optimized hybrid WTE system obtained by the proposed model achieves an optimal mix and balance of implemented treatment technologies, which is more practical than the current incineration only design in the MSW (municipal solid waste) management future in Singapore. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Waste-to-energy Feasibility analysis stochastic programming model

来源：评论

学校读者我要写书评

暂无评论

An optimization approach to the scale of port cold-chain dedicated terminals considering uncertainties

引用

ENGINEERING OPTIMIZATION 2022年第11期54卷 1887-1902页

作者： Ma, Qianli Ma, Baiyu He, Ying Sun, Weimeng Dalian Maritime Univ Sch Maritime Econ & Management Dalian Peoples R China Dalian Inst Sci & Technol Sch Transportat Dalian Peoples R China Minist Transport Peoples Republ China Water Transport Bur Beijing Peoples R China

As an important node of the international cold-chain logistics system, the special terminal for refrigerated ships is the core facility for cargo loading and unloading. To minimize the sum of construction costs and operating costs of dedicated cold-chain terminals, a stochastic programming model is established considering uncertainty of the type and time of arrival of refrigerated vessels and special requirements for cargo handling and storage, and the simulation optimization method based on tabu search is used to determine the optimal scale of cold-chain terminals. A case study on the port cold-chain system of an offshore fishery base is then presented to investigate the specific influence of uncertainties on the scale of cold-chain terminals. This provides a reference for scientific planning of cold-chain facilities and improving the efficiency of cold-chain systems in the sea-land exchange node.

关键词： stochastic programming model cold-chain infrastructure terminal scale system optimization

来源：评论

学校读者我要写书评

暂无评论

A Monte Carlo Optimization and Dynamic programming Approach for Managing MRI Examinations of Stroke Patients

引用

IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2011年第11期56卷 2515-2529页

作者： Geng, Na Xie, Xiaolan Augusto, Vincent Jiang, Zhibin Shanghai Jiao Tong Univ Shanghai 200240 Peoples R China Ecole Natl Super Mines F-42023 St Etienne France

Quick diagnosis is critical to stroke patients, but it relies on expensive and heavily used imaging equipment. This results in long waiting times with potential threats to the patient's life. It is important for neurovascular departments treating stroke patients to reduce waiting times for diagnosis. This paper proposes a reservation process of magnetic resonance imaging (MRI) examinations for stroke patients. The neurovascular department reserves a certain number of appropriately distributed contracted time slots (CTS) to ensure quick diagnosis of stroke patients. Additional MRI time slots can also be reserved by regular reservations (RTS). The problem consists in determining the contract and the control policy to assign patients to either CTS or RTS in order to reach the best compromise between the waiting times and unused CTS. Structural properties of the optimal control policy are proved by an average-cost Markov decision process (MDP) approach. The contract is determined by combining a Monte Carlo approximation approach and local search. Extensive numerical experiments are performed to show the efficiency of the proposed approach and to investigate the impact of different parameters.

关键词： Magnetic resonance imaging (MRI) Markov decision process (MDP) Monte Carlo optimization stochastic programming model stroke patients

来源：评论

学校读者我要写书评

暂无评论

Solving a bi-objective cell formation problem with stochastic production quantities by a two-phase fuzzy linear programming approach

引用

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2012年第5-8期58卷 709-722页

作者： Rabbani, Masoud Jolai, Fariborz Manavizadeh, Neda Radmehr, Farzad Javadi, Babak Univ Tehran Coll Engn Dept Ind Engn Tehran Iran

We propose a bi-objective cell formation problem with demand of products expressed in a number of probabilistic scenarios. To deal with the uncertain demand of products, a framework of two-stage stochastic programming model is presented. The proposed model considers minimizing the sum of the miscellaneous costs (machine constant cost, expected machine variable cost, cell fixed-charge cost, and expected intercell movement cost) and expected total cell loading variation. Because of conflicting objectives, we develop a two-phase fuzzy linear programming approach for solving bi-objective cell formation problem. To show the effectiveness of the proposed approach, numerical examples are solved and the results are compared with the two existing approaches in the literature. The computational results show that the proposed fuzzy method achieves lower objective functions as well as higher satisfaction degrees.

关键词： Cellular manufacturing design Cell formation problem Multi-objective Fuzzy linear programming stochastic programming model

来源：评论

学校读者我要写书评

暂无评论

Emergency medical service planning considering dynamic and stochastic demands of infected and non-infected patients during epidemics

引用

JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 2024年第4期75卷 705-719页

作者： Luo, Li Wang, Yikun Jiang, Peng Zhuo, Maolin Wang, Qingyi Sichuan Univ Business Sch Chengdu Peoples R China Chengdu Ind & Trade Coll Sch Finance & Trade Management Chengdu Peoples R China Sichuan Univ Business Sch Chengdu 610064 Peoples R China

During a large-scale epidemic, a local healthcare system can be overwhelmed by a large number of infected and non-infected patients. To serve the infected and non-infected patients well with limited medical resources, effective emergency medical service planning should be conducted before the epidemic. In this study, we propose a two-stage stochastic programming model, which integrally deploys various types of emergency healthcare facilities before an epidemic and serves infected and non-infected patients dynamically at the deployed healthcare facilities during the epidemic. With the service equity of infected patients and various practical requirements of emergency medical services being explicitly considered, our model minimizes a weighted sum of the expected operation cost and the equity cost. We develop two comparison models and conduct a case study on Chengdu, a Chinese city influenced by the COVID-19 epidemic, to show the effectiveness and benefits of our proposed model. Sensitivity analyses are conducted to generate managerial insights and suggestions. Our study not only extends the existing emergency supply planning models but also can facilitate better practices of emergency medical service planning for large-scale epidemics.

关键词： stochastic programming model emergency medical service infected and non-infected patients dynamic and stochastic demands epidemics

来源：评论

学校读者我要写书评

暂无评论

Additive manufacturing of biomedical implants: A feasibility assessment via supply-chain cost analysis

引用

ADDITIVE MANUFACTURING 2016年 11卷 97-113页

作者： Emelogu, Adindu Marufuzzaman, Mohammad Thompson, Scott M. Shamsaei, Nima Bian, Linkan Mississippi State Univ Analyt & Optimizat Lab Dept Ind & Syst Engn Mississippi State MS 39762 USA Mississippi State Univ Dept Mech Engn Mississippi State MS 39762 USA Mississippi State Univ Ctr Adv Vehicular Syst Mississippi State MS 39762 USA

The adoption of additive manufacturing (AM) for fabricating biomedical implants at hospitals provides many potential benefits. Relative to biomedical implants fabricated via traditional manufacturing (TM), typically available by suppliers out of the immediate region, biomedical implants fabricated through AM provides an opportunity to receive more patient-specific, customized parts with faster response, a lower inventory level, and reduced delivery costs. Despite the promising features of AM technologies, the make-or-buy decisions are not straightforward and require careful investigation due to the relatively high AM machine and production costs. Most of the existing studies focus on the analysis of process-level costs, which are usually evaluated/calculated based on individual AM processes. No research efforts, to the best of our knowledge, have been dedicated to the quantitative analysis of the costs of supply chains integrated with AM facilities, e.g., inventory cost, transportation cost, product lead time, etc. In this study, we propose a stochastic cost model to quantify the supply-chain level costs associated with the production of biomedical implants using AM techniques, and investigate the economic feasibility of using such technologies to fabricate biomedical implants at the sites of hospitals. The problem is formulated in the form of a stochastic programming model, which determines the number of AM facilities to be established and volume of product flow between manufacturing facilities and hospitals. A customized Sample Average Algorithm (SAA) is developed to obtain the solutions. We apply the cost model to a real-world case study that focuses on the use of biomedical implants for hospitals in the state of Mississippi (MS), and identify the conditions and cost parameters that have significant impact on the economic feasibility of AM. We find that the ratio between the unit production costs of AM and TM (ATR), as well as product lead time and demands, are k

关键词： Additive manufacturing Supply chain Cost analysis Biomedical implants stochastic programming model

来源：评论

学校读者我要写书评

暂无评论

Real-time energy management of a smart virtual power plant

引用

IET GENERATION TRANSMISSION & DISTRIBUTION 2019年第11期13卷 2015-2023页

作者： Rahimiyan, Morteza Baringo, Luis Shahrood Univ Technol Dept Elect Engn Shahrood Iran Univ Castilla La Mancha Dept Elect Engn Ciudad Real Spain

The real-time (RT) energy management of virtual power plants (VPPs) is a complex problem due to the coordinated operation of diverse energy resources and their associated uncertainties. This article presents a comparative analysis on alternative energy management models for a VPP that includes a wind power unit, an energy storage unit, and some flexible demands, which are interconnected within a small size electric energy system. The smart grid technology enables RT operation of the VPP by taking advantage of bidirectional communication infrastructure. To accomplish this task, the RT energy management is implemented through alternative decision-making tools, namely, (i) a robust model, (ii) a stochastic programming model, and (iii) a stochastic robust model. To handle uncertainties, these optimisation models use prediction intervals, scenarios, and a combination of both, respectively. A realistic case study provides a comparative out-of-sample analysis considering the impact of the different parameters used to manage risk in these three models.

关键词： energy management systems smart power grids power generation economics power system interconnection wind power plants stochastic programming risk management decision making real-time energy management smart virtual power plant diverse energy resources associated uncertainties wind power unit energy storage unit small size electric energy system smart grid technology RT operation bidirectional communication infrastructure RT energy management alternative decision-making tools robust model stochastic programming model stochastic robust model optimisation models prediction intervals risk management

来源：评论

学校读者我要写书评

暂无评论

Relief supply collaboration for emergency logistics responses to large-scale disasters

引用

TRANSPORTMETRICA A-TRANSPORT SCIENCE 2015年第3期11卷 210-242页

作者： Sheu, Jiuh-Biing Pan, Cheng Natl Taiwan Univ Dept Business Adm Taipei 106 Taiwan

This paper proposes a novel relief supply collaboration approach to address the issue of post-disaster relief supply-demand imbalance in emergency logistics (EL) operations. This proposed approach involves two levels of recursive functions: (1) a two-stage relief supplier clustering mechanism for time-varying multi-source relief supplier selection and (2) the use of stochastic dynamic programming model to determine a multi-source relief supply that minimises the impact of relief supply-demand imbalance during EL response. The distinctive features of this proposed approach are to identify the potential relief suppliers and to minimise the imbalanced supply-demand impact under relief supply collaboration. Scenario design and model tests are conducted to demonstrate that relief supply collaboration with grouped relief suppliers has a significant benefit of alleviating the impact of imbalanced relief supply-demand, relative to collaboration with ungrouped ones.

关键词： relief supplier selection relief supply-demand imbalance stochastic programming model fuzzy clustering emergency logistics

来源：评论

学校读者我要写书评

暂无评论

A stochastic programming approach to determine robust delivery profiles in area forwarding inbound logistics networks

引用

OR SPECTRUM 2013年第4期35卷 807-834页

作者： Schoeneberg, Tim Koberstein, Achim Suhl, Leena Univ Paderborn D-33098 Paderborn Germany Goethe Univ Frankfurt D-60323 Frankfurt Germany

One technique to coordinate the suppliers' and the producers' production plans in a supply chain is the use of delivery profiles, which provide fixed delivery frequencies for all suppliers. The selection of a delivery profile assignment has major effects on the cost efficiency and the robustness of a supply chain and thus should be performed carefully. In this work, we consider planning approaches to select delivery profiles for the case of area forwarding-based inbound logistics networks, which are commonly used in several industries to consolidate supplies in an early stage of transport. We present a two-stage stochastic mixed integer linear programming model to determine robust delivery profile assignments under uncertain and infrequent demands and complex tariff systems. The model is embedded into a solution framework consisting of scenario generation and reduction techniques, a decomposition approach, a genetic algorithm, and a standard MILP solver. On the basis of an industrial case study, we show that our approach is computationally feasible and that the planning solutions obtained by our model outperform both a deterministic approach and the planning methodology prevailing in industrial practice.

关键词： Procurement planning Delivery profiles Automotive industry stochastic programming model

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：