检索结果-内蒙古大学图书馆

Resource allocation and route planning under the collection price uncertainty for the biomass supply chain

BIOSYSTEMS ENGINEERING 2024年 241卷 68-82页

作者： Wang, Xiang Ting Cao, Jin Xin Lv, Ying Beijing Jiaotong Univ Sch Syst Sci Beijing 100044 Peoples R China Inner Mongolia Acad Sci & Technol Hohhot 010010 Peoples R China Inner Mongolia Univ Inst Transportat Engn Hohhot 010070 Peoples R China

The escalating severity of global warming has drawn worldwide attention to ecological problems. Nevertheless, with the introduction of environmental policies, biomass resources have been effectively developed as a renewable energy source. This paper investigates an advanced biomass supply chain design wherein biomass resources are initially converted into bio-oil through widely distributed fast pyrolysis facilities, and are subsequently transported to a centralised biorefinery for further refining into biofuels. This novel biomass supply chain addressed three key issues: (1) The number of fast pyrolysis facilities, (2) The allocation of resources, and (3) The routes of resources transport. In respect of these problems, a two-stage stochastic mixed integer programming model is established to minimise the total cost of the biomass supply chain considering the uncertainty collection price of fast pyrolysis facilities. A hybrid simulated annealing algorithm which incorporates the sample average approximation method is proposed to solve the stochastic model and is effectiveness for large-scale examples. Finally, a sensitivity analysis is performed using the proposed algorithm and the results show that the proposed stochastic model outperforms the deterministic model under uncertain collection price. The model allows optimising the biomass supply chain economic performances and minimise financial risk on investment by determining the fast pyrolysis facility locations, reasonable resource allocation and optimal transport routes under uncertain collection price.

关键词： stochastic programming Mixed integer programming model Hybrid simulated annealing algorithm Sample average approximation

来源：评论

学校读者我要写书评

暂无评论

Efficiency assessment of public sector management and culture-led urban regeneration using the enhanced Russell-based directional distance function with stochastic data

引用

JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 2024年第8期75卷 1624-1642页

作者： Lin, Sheng-Wei Lu, Wen-Min Natl Def Univ Dept Financial Management Taipei Taiwan Chinese Culture Univ Dept Int Business Adm Taipei Taiwan Natl Def Univ Taipei Taiwan

Generic data envelopment analysis (DEA) models are based on deterministic input and output. However, input and output vectors are often interrupted by random factors, such as measurement errors and data noise, in real economic situations. This study proposes a new chance-constrained network DEA model based on the modified directional distance function (DDF) and enhanced Russell measure (ERM) model for assessing government management and culture-led urban regeneration. In addition to exploring the randomness of data, this study integrates the advantages of both ERM and DDF and considers the inefficiency level from a non-oriented viewpoint, the direction vector, and each input and output simultaneously. Each input and output of the two production stages can use non-radials to measure efficiency. Results show that the urban-rural gap has gradually widened since 2015. To validate the legitimacy of the model, this study utilizes the bootstrapping method to verify the results of the stochastic network DEA model and the conventional two-stage network DEA approach. This study also considers different alpha values as basis for comparison to confirm whether the results obtained differ by uncertainty level.

关键词： Data envelopment analysis decision analysis performance evaluation stochastic programming

来源：评论

学校读者我要写书评

暂无评论

A new approach for reliability modeling in green closed-loop supply chain design under post-pandemic conditions: A case study

引用

COMPUTERS & CHEMICAL ENGINEERING 2024年 189卷

作者： Izadian, Amir Bahador Pasandideh, Seyed Hamid Reza Abad, Amin Reza Kalantari Khalil Kharazmi Univ Fac Engn Dept Ind Engn Tehran Iran Iran Univ Sci & Technol Sch Ind Engn Tehran Iran

Climate change, pandemics, and economic crises have created complex challenges for supply chains. Managing such situations requires the development of reliable decision-making frameworks. In this paper, a multi-level, multi-product, and multi-period closed-loop supply chain is studied with environmental considerations. A biobjective mixed-integer linear programming model is presented for facility location, flow allocation, and transportation mode determination. The objectives of the model are to minimize the total cost and maximize the reliability of suppliers to meet the needs of factories. In the area of reliability engineering, a new approach is defined for modeling the probability of supplier availability considering catastrophic failures caused by pandemics, economic sanctions, and other failure modes. Furthermore, the decision-maker can handle the emission of greenhouse gases by an upper-bound constraint. In order to face the simultaneous uncertainty of demand and the maximum CO2 2 emission allowed, a scenario-based two-stage stochastic programming approach is proposed. The improved version of the augmented epsilon-constraint method, known as AUGMECON2, is used to solve the proposed model. The efficiency of the model and the proposed solution approach are investigated through a real- world case study of a battery manufacturing company in Iran.

关键词： Supply chain network design Circular supply chain Reliability stochastic programming Augmented epsilon-constraint

来源：评论

学校读者我要写书评

暂无评论

A multi-stage framework for coordinated scheduling of networked microgrids in active distribution systems with hydrogen refueling and charging stations

引用

INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2024年 71卷 1442-1455页

作者： Parsibenehkohal, Reza Jamil, Mohsin Khan, Ashraf Ali Mem Univ Newfoundland Fac Engn & Appl Sci Dept Elect & Comp Engn St John NF A1B 5S7 Canada

Due to the increase in electric energy consumption and the significant growth in the number of electric vehicles (EV) at the level of the distribution network, new networks have started using new fuels such as hydrogen to improve environmental indicators and at the same time better efficiency from the excess capacity of renewable resources. In this article, the services that can be provided by hydrogen refueling stations and charging electric vehicles in the optimal performance of microgrids have been investigated. The model proposed in this paper includes a two-stage stochastic framework for scheduling resources in microgrids, especially hydrogen refueling stations and electric vehicle charging. In this model, two main goals of cost minimization and greenhouse gas emissions are considered. In the proposed framework and in the first stage, the service range of microgrids is determined precisely according to the electrical limitations of distribution systems in emergency situations. Then, in the second stage, the problem of energy management in each microgrid will be solved centrally. In this situation, various indicators including the output energy of renewable sources, smart charging of hydrogen and electric vehicle charging stations (EV/FCV) and flexible loads (FL) are evaluated. The final mathematical model is implemented as a multivariate integer multiple linear problem (MILP) using the GUROBI solver in GAMS software. The simulation results on the modified IEEE 118-Bus network show the positive effect of the presence of flexible loads and smart charging strategies by charging stations. Also, the numerical derivation shows that the operating costs of the entire system can be reduced by 4.77% and the use of smart charging strategies can reduce greenhouse gas emissions by 49.13%.

关键词： stochastic programming Active distribution system Networked microgrids Electric vehicle charging stations Hydrogen refueling stations Multi-objective optimization

来源：评论

学校读者我要写书评

暂无评论

Eco-environmental regret-aware optimization of networked multi-energy microgrids with fully carbon elimination and electric vehicles' promotion

引用

SUSTAINABLE CITIES AND SOCIETY 2024年 115卷

作者： Deng, Zhuofu Zheng, Yingnan Zhang, Jiaqi Liu, Peng Zhu, Zhiliang Northeastern Univ Software Coll Shenyang 110819 Peoples R China State Grid Liaoning Elect Power Co Ltd Shenyang Power Supply Co Shenyang 110002 Peoples R China China Elect Power Res Inst State Grid Co Ltd Beijing 100192 Peoples R China

With the escalating concern of global warming propelled by the rise in Earth's temperature, the need for effective CO2 management has become crucial. This paper presents an innovative CO2 elimination approach, wherein a multiple integrated system of energies (MISEs) incorporating sustainable resources, including renewable resources (RENs), plug-in electric vehicles (PEVs), and demand response programs, is optimized. The proposed carbon elimination framework begins by modeling the onsite carbon capturing and recycling within each MISE. To effectively utilize the onsite carbon recycling facilities and achieve carbon neutrality, the proposed model also incorporates carbon transfer capability between MISEs, thereby enhancing the efficiency of overall carbon recycling. Furthermore, a stochastic p-robust optimization technique is proposed to effectively manage uncertainties by combining the advantages of stochastic programming and robust optimization. This uncertainty modeling approach promotes greater utilization of sustainable resources like PEVs and RENs due to their lower operational regrets from economic and environmental perspectives. Based on the simulation results, implementing the p-robust-based regret assessment technique led to the total operation cost increasing by only 2.75 %, while achieving a significant 44.5 % reduction in maximum relative regret. These results underscore the effectiveness of the proposed framework in enhancing both the economic and environmental performance of MISEs.

关键词： Carbon elimination Carbon transaction Electric vehicle promotion Multi energy transactive multi-microgrids P -robust regret assessment stochastic programming

来源：评论

学校读者我要写书评

暂无评论

Simple subvector inference on sharp identified set in affine models

引用

JOURNAL OF ECONOMETRICS 2025年 29卷

作者： Gafarov, Bulat Univ Calif Davis Dept Agr & Resource Econ Davis CA 95616 USA

This paper studies a regularized support function estimator for bounds on components of the parameter vector in the case in which the identified set is a polygon. The proposed regularized estimator has three important properties: (i) it has a uniform asymptotic Gaussian limit in the presence of flat faces in the absence of redundant (or overidentifying) constraints (or vice versa);(ii) the bias from regularization does not enter the first-order limiting distribution;(iii) the estimator remains consistent for sharp (non-enlarged) identified set for the individual components even in the non-regular case. These properties are used to construct uniformly valid confidence sets for an element theta 1 of a parameter vector theta is an element of Rd that is partially identified by affine moment equality and inequality conditions. The proposed confidence sets can be computed as a solution to a small number of linear and convex quadratic programs, leading to a substantial decrease in computation time and guarantees a global optimum. As a result, the method provides a uniformly valid inference in applications in which the dimension of the parameter space, d, and the number of inequalities, k, were previously computationally unfeasible (d , k = 100). The proposed approach can be extended to construct confidence sets for intersection bounds, to construct joint polygon-shaped confidence sets for multiple components of theta, and to find the set of solutions to a linear program. Inference for coefficients in the linear IV regression model with an interval outcome is used as an illustrative example.

关键词： Affine-moment inequalities Asymptotic linear representation Higher-order analysis Delta method Interval data Intersection bounds Partial identification Regularization Strong approximation stochastic programming Subvector inference Uniform inference

来源：评论

学校读者我要写书评

暂无评论

Dynamic Scheduling Optimization of Automatic Guide Vehicle for Terminal Delivery under Uncertain Conditions

引用

APPLIED SCIENCES-BASEL 2024年第18期14卷 8101页

作者： Shao, Qianqian Miao, Jiawei Liao, Penghui Liu, Tao Shenyang Jianzhu Univ Sch Transportat Engn Shenyang 110168 Peoples R China

As an important part of urban terminal delivery, automated guided vehicles (AGVs) have been widely used in the field of takeout delivery. Due to the real-time generation of takeout orders, the delivery system is required to be extremely dynamic, so the AGV needs to be dynamically scheduled. At the same time, the uncertainty in the delivery process (such as the meal preparation time) further increases the complexity and difficulty of AGV scheduling. Considering the influence of these two factors, the method of embedding a stochastic programming model into a rolling mechanism is adopted to optimize the AGV delivery routing. Specifically, to handle real-time orders under dynamic demand, an optimization mechanism based on a rolling scheduling framework is proposed, which allows the AGV's route to be continuously updated. Unlike most VRP models, an open chain structure is used to describe the dynamic delivery path of AGVs. In order to deal with the impact of uncertain meal preparation time on route planning, a stochastic programming model is formulated with the purpose of minimizing the expected order timeout rate and the total customer waiting time. In addition, an effective path merging strategy and after-effects strategy are also considered in the model. In order to solve the proposed mathematical programming model, a multi-objective optimization algorithm based on a NSGA-III framework is developed. Finally, a series of experimental results demonstrate the effectiveness and superiority of the proposed model and algorithm.

关键词： AGV takeout terminal delivery rolling scheduling stochastic programming routing combination NSGA-III

来源：评论

学校读者我要写书评

暂无评论

A C plus plus application programming interface for co-evolutionary biased random-key genetic algorithms for solution and scenario generation

引用

OPTIMIZATION METHODS & SOFTWARE 2022年第3期37卷 1065-1086页

作者： Oliveira, Beatriz Brito Carravilla, Maria Antonia Oliveira, Jose Fernando Resende, Mauricio G. C. Univ Porto INESC TEC Fac Engn Porto Portugal Amazon Com Inc Bellevue WA USA Univ Washington Ind & Syst Engn Seattle WA 98195 USA

This paper presents a C++ application programming interface for a co-evolutionary algorithm for solution and scenario generation in stochastic problems. Based on a two-space biased random-key genetic algorithm, it involves two types of populations that are mutually impacted by the fitness calculations. In the solution population, high-quality solutions evolve, representing first-stage decisions evaluated by their performance in the face of the scenario population. The scenario population ultimately generates a diverse set of scenarios regarding their impact on the solutions. This application allows the straightforward implementation of this algorithm, where the user needs only to define the problem-dependent decoding procedure and may adjust the risk profile of the decision-maker. This paper presents the co-evolutionary algorithm and structures the interface. We also present some experiments that validate the impact of relevant features of the application.

关键词： Genetic algorithm application programming interface stochastic programming scenario generation co-evolutionary algorithm

来源：评论

学校读者我要写书评

暂无评论

A multi period and multi objective stochastic hydrogen supply chain for Turkey

引用

INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2025年 107卷 618-631页

作者： Ozbek, Busenur Turkali Guler, Mehmet Guray Yildiz Tech Univ Fac Mech Engn Dept Ind Engn Istanbul Turkiye Istanbul Tech Univ Fac Management Dept Ind Engn Istanbul Turkiye

The energy sources that are used intensively in vehicles are generally non-renewable energy sources and they are in danger of being depleted as demand increases. To deal with this, countries are turning to hydrogen, which is considered a clean and renewable energy source. For hydrogen to be widespread, the Hydrogen Supply Chain (HSC) should be planned effectively. There are three key issues associated with an HSC. First, the uncertainty of future demand makes it difficult to design an HSC. Second, considering only the cost can bring along many other problems. One should also consider the associated risk and CO2 emission as well. Third, in addition to the steady state of HSC, the transition of the HSC throughout periods is also important. In this study, a multi-objective, multi-period stochastic model is proposed to address these three issues. The results show that facilities having low CO2 emission are opened in northern region of Turkey because of H2S sources in Black Sea and they serve the center and the eastern regions. The west and south, focus on more cost-effective solutions due to high population.

关键词： Hydrogen supply chain stochastic programming Renewable energy source Multi-objective

来源：评论

学校读者我要写书评

暂无评论

The impact of pumped hydro energy storage configurations on investment planning of hybrid systems with renewables

引用

RENEWABLE ENERGY 2024年 222卷

作者： Yurter, Gulin Nadar, Emre Kocaman, Ayse Selin Bilkent Univ Dept Ind Engn Ankara Turkiye MIT Energy Initiat Cambridge MA USA

The pumped hydro energy storage (PHES) systems can be installed in various configurations depending on the specific geographical and hydrological conditions. Closed -loop PHES systems are off -stream and have no natural inflow to the system. However, open -loop systems are on -stream and have natural inflows to the upper and/or lower reservoirs. In this study, we develop two -stage stochastic programming models for various PHES configurations to investigate how the choice of PHES configuration impacts the sizing decisions and costs of a hybrid system that includes a renewable power generator co-operated with PHES. Our numerical results show that using a PHES facility instead of a conventional hydropower system reduces the expected system cost and mismatched demand significantly. Open -loop PHES facilities perform better than closed -loop PHES and seawater-PHES facilities, dramatically lowering the need for fossil fuels in demand fulfillment. The most cost-efficient PHES configuration is when there is natural inflow to the upper reservoir. Using solar energy instead of wind as the renewable source significantly increases the requirement for larger upper reservoirs in on -stream open -loop PHES facilities, while reducing the expected system cost for all configurations.

关键词： Pumped hydro energy storage Renewable energy stochastic programming Hybrid energy systems Investment planning

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：