检索结果-内蒙古大学图书馆

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

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

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

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

引用

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

Topology optimization of random memristors for input-aware dynamic SNN

引用

SCIENCE ADVANCES 2025年第16期11卷 eads5340页

作者： Wang, Bo Zhang, Xinyuan Wang, Shaocong Lin, Ning Li, Yi Yu, Yifei Zhang, Yue Yang, Jichang Wu, Xiaoshan He, Yangu Wang, Songqi Wan, Tao Chen, Rui Li, Guoqi Deng, Yue Qi, Xiaojuan Wang, Zhongrui Shang, Dashan Univ Hong Kong Dept Elect & Elect Engn Hong Kong Peoples R China ACCE SS AI Chip Ctr Emerging Smart Syst InnoHK Ctr Hong Kong Sci Pk Hong Kong Peoples R China Chinese Acad Sci Inst Microelect State Key Lab Fabricat Technol Integrated Circuits Beijing 100029 Peoples R China Chinese Acad Sci Inst Microelect Lab Microelect Devices & Integrated Technol Beijing 100029 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Chinese Acad Sci Inst Automat Key Lab Brain Cognit & Brain Inspired Intelligence Beijing 100190 Peoples R China Beihang Univ Sch Artificial Intelligence Beijing 100191 Peoples R China Beihang Univ Sch Astronaut Beijing 100191 Peoples R China

Machine learning has advanced unprecedentedly, exemplified by GPT-4 and SORA. However, they cannot parallel human brains in efficiency and adaptability due to differences in signal representation, optimization, runtime reconfigurability, and hardware architecture. To address these challenges, we introduce pruning optimization for input-aware dynamic memristive spiking neural network (PRIME). PRIME uses spiking neurons to emulate brain's spiking mechanisms and optimizes the topology of random memristive SNNs inspired by structural plasticity, effectively mitigating memristor programming stochasticity. It also uses the input-aware early-stop policy to reduce latency and leverages memristive in-memory computing to mitigate von Neumann bottleneck. Validated on a 40-nm, 256-K memristor-based macro, PRIME achieves comparable classification accuracy and inception score to software baselines, with energy efficiency improvements of 37.8x and 62.5x. In addition, it reduces computational loads by 77 and 12.5% with minimal performance degradation and demonstrates robustness to stochastic memristor noise. PRIME paves the way for brain-inspired neuromorphic computing.

关键词： stochastic programming

来源：评论

学校读者我要写书评

暂无评论

Coordinated Planning for Multiarea Wind-Solar-Energy Storage Systems That Considers Multiple Uncertainties

引用

ENERGIES 2024年第21期17卷

作者： Wu, Weijie Li, Yixin Wang, Shu Wang, Zheng Zhou, Shucan Zhang, Yining Zheng, Minjia Guangdong Power Grid Corp Guangdong Power Grid Planning Res Ctr Guangzhou 510062 Peoples R China China Elect Power Res Inst Natl Key Lab Renewable Energy Grid Integrat Beijing 100192 Peoples R China Peking Univ Sch Phys Beijing 100871 Peoples R China

As the scale of renewable energy sources (RESs) expands, it is essential to optimize the configuration of wind, solar, and storage resources across different areas. Nevertheless, the unavoidable uncertainties associated with both energy supply and demand present significant challenges for planners. This study aims to address the challenge of coordinated planning for multiarea wind-solar-energy storage systems considering multiple uncertainties. First, uncertainties related to future peak demand, thermal generation output boundaries, demand variability, and stochastic unit production are analyzed and modeled on the basis of robust optimization and stochastic programming techniques. Then, a hierarchical coordinated planning model that incorporates both system-wide (SW) and local area (LA) planning models is proposed. The SW planning model is designed to manage the optimal capacity configuration of RESs and energy storage systems (ESSs) within each LA, as well as the operational boundary of LAs. The LA planning models aim to further optimize the capacities of RESs and ESSs and minimize the economic cost within each LA on the basis of local resource characteristics. To achieve the optimal solution, the analytical target cascading (ATC) algorithm is integrated with the column-and-constraint generation (C&CG) algorithm. The simulation results validate the effectiveness and reasonableness of the proposed coordinated planning model, which not only outperforms independent planning approaches but also effectively manages the uncertainties.

关键词： coordinated planning renewable energy source energy storage system robust optimization stochastic programming uncertainty

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

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

Multi-period hub network design from a dual perspective: An integrated approach considering congestion, demand uncertainty, and service quality optimization

引用

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2025年第1期326卷 78-95页

作者： Bayram, Vedat Aydogan, Ciya Kargar, Kamyar Univ Kent Ctr Logist & Sustainabil Analyt Kent Business Sch Dept Analyt Operat & Syst Canterbury Kent England TED Univ Dept Ind Engn Ankara Turkiye Middle East Tech Univ Dept Ind Engn Ankara Turkiye Univ Lancaster Management Sch Dept Management Sci Lancaster LA1 4YX England

This study introduces a hub network design problem that considers three key factors: congestion, demand uncertainty, and multi-periodicity. Unlike classical models, which tend to address these factors separately, our model considers them simultaneously, providing a more realistic representation of hub network design challenges. Our model also incorporates service level considerations of network users, extending beyond the focus on transportation costs. Service quality is evaluated using two measures: travel time and the number of hubs visited during travel. Moreover, our model allows for adjustments in capacity levels and network structure throughout the planning horizon, adding a dynamic and realistic aspect to the problem setting. The inherent nonlinear nonconvex integer programming problem is reformulated into a mixed-integer second-order cone programming (SOCP) problem. To manage the model's complexity, we propose an exact solution algorithm based on Benders decomposition, where the sub-problems are solved using a column generation technique. The efficacy of the solution approach is demonstrated through extensive computational experiments. Additionally, we discuss the benefits of each considered feature in terms of transportation costs and their impact on network structure, providing insights for the field.

关键词： Location Congestion stochastic programming Multi-period Service level Second-order cone programming Benders decomposition Column generation

来源：评论

学校读者我要写书评

暂无评论

Multi-horizon stochastic programming

引用

COMPUTATIONAL MANAGEMENT SCIENCE 2014年第1-2期11卷 179-193页

作者： Kaut, Michal Midthun, Kjetil T. Werner, Adrian S. Tomasgard, Asgeir Hellemo, Lars Fodstad, Marte SINTEF Technol & Soc Dept Appl Econ & Operat Res Trondheim Norway Norwegian Univ Sci & Technol NTNU Dept Ind Econ & Technol Management Trondheim Norway

Infrastructure-planning models are challenging because of their combination of different time scales: while planning and building the infrastructure involves strategic decisions with time horizons of many years, one needs an operational time scale to get a proper picture of the infrastructure's performance and profitability. In addition, both the strategic and operational levels are typically subject to significant uncertainty, which has to be taken into account. This combination of uncertainties on two different time scales creates problems for the traditional multistage stochastic-programming formulation of the problem due to the exponential growth in model size. In this paper, we present an alternative formulation of the problem that combines the two time scales, using what we call a multi-horizon approach, and illustrate it on a stylized optimization model. We show that the new approach drastically reduces the model size compared to the traditional formulation and present two real-life applications from energy planning.

关键词： stochastic programming Multistage Energy planning Scenario tree construction

来源：评论

学校读者我要写书评

暂无评论

Capacity planning with uncertainty on contract fulfillment

引用

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2024年第1期314卷 152-175页

作者： Crainic, Teodor Gabriel Perboli, Guido Rei, Walter Rosano, Mariangela Lerma, Veronica Univ Quebec Montreal UQAM Sch Management Sci CP 8888 Succ Ctr ville Montreal PQ H3C 3P8 Canada Univ Montreal CIRRELT Interuniv Res Ctr Enterprise Networks PO 6120 Succ Ctr Ville Montreal PQ H3C 3J7 Canada DIGEP Politecn Torino Corso Duca Abruzzi 24 I-10129 Turin Italy

This paper focuses on the tactical planning problem faced by a shipper which seeks to secure transportation and warehousing capacity, such as containers, vehicles or space in a warehouse, of different sizes, costs, and characteristics, from a carrier or logistics provider, while facing different sources of uncertainty. The uncertainty can be related to the loads to be transported or stored, the cost and availability of ad-hoc capacity on the spot market in the future, and the availability of the contracted capacity in the future when the shipper needs it. This last source of uncertainty on the capacity loss on the contracted capacity is particularly important in both long-haul transportation and urban distribution applications, but no optimization methodology has been proposed so far. We introduce the stochastic Variable Cost and Size Bin Packing with Capacity Loss problem and model that directly address this issue, together with a metaheuristic to efficiently address it. We perform a set of extensive numerical experiments on instances related to long-haul transportation and urban distribution contexts and derive managerial insights on how such capacity planning should be performed. (c) 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license ( http://***/licenses/by/4.0/ )

关键词： Supply chain management Logistics capacity planning stochastic programming City logistics Long-haul freight transportation

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：