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Synthesis of refinery hydrogen network considering compressor selection and interstage suction/discharge

INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2023年第91期48卷 35419-35432页

作者： Zhou, Yingqian Wang, Yufei Feng, Xiao Yang, Minbo Xi An Jiao Tong Univ Sch Chem Engn & Technol 28 Xianning West Rd Xian 710049 Shaanxi Peoples R China China Univ Petr State Key Lab Heavy Oil Proc Beijing Peoples R China

In refinery hydrogen networks, the optimal arrangement of hydrogen compressors is important to hydrogen reuse and cost reduction. The share of hydrogen compressors can not only reduce the number of compressors, but also provide the economy of scale. However, the previous studies only consider the whole share of compressors and mostly treat the compressor model as reciprocating compressors by default, which limits the optimization of hydrogen networks and does not correspond well with the practice. This paper presents a novel method for hydrogen network synthesis considering the hydrogen compressor type selection and the interstage suction/discharge of multi-stage compressors. In the developed superstructure, hydrogen sources are allowed to be suctioned and discharged via all possible stages of multi-stage compressors. Meanwhile, hydrogen sources can select centrifugal compressors or reciprocating compressors according to the working ranges. A mixed integer nonlinear programming model is developed to minimize the total annualized cost. The proposed method is suitable for both retrofit problems and new design problems, which is demonstrated by a refinery case and a literature case. For the refinery case, the zero-investment retrofit based on the existing compressors can reduce the fresh hydrogen demand by 1.73%, and the new hydrogen network design re-quires fewer compressors. In terms of the literature case, the hydrogen network design obtained in this paper can reduce the number of compressors by 5 or 3 through interstage suction/discharge of multi-stage compressors.(c) 2023 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

关键词： Hydrogen network Compressor share Interstage suction/discharge Compressor type selection mixed integer nonlinear programming

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Mathematical programming model of process plant safety layout using the equipment vulnerability index

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KOREAN JOURNAL OF CHEMICAL ENGINEERING 2023年第4期40卷 727-739页

作者： Guo, Liping Wang, Zhirong Guo, Pinkun Wang, Jinghong Zhao, Dan Nanjing Tech Univ Coll Safety Sci & Engn Nanjing 211816 Peoples R China Lanzhou Univ Technol Sch Petrochem Engn Lanzhou 730050 Peoples R China

Safety is the focus of attention in plant layout problems. Previous studies have often expressed safety as a cost of risk, that is, the cost of property losses that may occur in an accident. In this paper, the influence of uncertainty on the equipment vulnerability is quantitatively considered and a more reliable process plant layout is proposed. The equipment vulnerability index is used to evaluate the vulnerability level of the target equipment in case of an accident, which is applied to propose a mixed-integer nonlinear optimized process plant layout to minimize domino risk. In addition, a decision matrix is applied to determine whether the risk level of the optimized layout of the target equipment is acceptable. Damage probability and vulnerability are the basic inputs of this matrix. The proposed method was applied to a coal-water slurry gasification process and the results show that the layout obtained by the proposed model has better practical value than the current layout, reducing the domino risk by 53.2%. Meanwhile, the model can be used to identify critical equipment and select targeted safety measures during the production stage.

关键词： Fuzzy Comprehensive Evaluation Equipment Vulnerability Index mixed integer nonlinear programming Layout Optimization Decision Matrix

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Alternating Direction Method and Deep Learning for Discrete Control with Storage 8th

Alternating Direction Method and Deep Learning for Discrete ...

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8th International Symposium on Combinatorial Optimization (ISCO)

作者： Demassey, Sophie Sessa, Valentina Tavakoli, Amirhossein Mines Paris PSL Ctr Appl Math Paris France Univ Cote dAzur Nice France

ISBN: (纸本)9783031609237;9783031609244

This paper deals with scheduling the operations in systems with storage modeled as a mixed integer nonlinear program (MINLP). Due to time interdependency induced by storage, discrete control, and nonlinear operational conditions, computing even a feasible solution may require an unaffordable computational burden. We exploit a property common to a broad class of these problems to devise a decomposition algorithm related to alternating direction methods, which progressively adjusts the operations to the storage state profile. We also design a deep learning model to predict the continuous storage states to start the algorithm instead of the discrete decisions, as commonly done in the literature. This enables search diversification through a multi-start mechanism and prediction using scaling in the absence of a training set. Numerical experiments on the pump scheduling problem in water networks show the effectiveness of this hybrid learning/decomposition algorithm in computing near-optimal strict-feasible solutions in more reasonable times than other approaches.

关键词： mixed integer nonlinear programming Variable splitting Deep Learning

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A hybrid differential evolution algorithm for a location-inventory problem in a closed-loop supply chain with product recovery

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COMPLEX & INTELLIGENT SYSTEMS 2023年第4期9卷 4123-4145页

作者： Guo, Hao Liu, Gang Zhang, Ying Zhang, Chunnan Xiong, Chuanhui Li, Wenli Wuhan Text Univ Sch Management Wuhan 430200 Hubei Peoples R China Hubei Univ Econ Collaborat Innovat Ctr Emiss Trading Syst Coconstr Wuhan 430200 Hubei Peoples R China Hubei Univ Econ Sch Business Adm Wuhan 430200 Hubei Peoples R China SUNY Buffalo Dept Ind & Syst Engn Buffalo NY 14260 USA State Univ New York Plattsburgh Dept Accounting Plattsburgh NY 12901 USA Univ North Carolina Pembroke Thomas Sch Business Pembroke NC 28372 USA Univ Hubei Prov Key Res Inst Humanities & Social Sci Res Ctr Enterprise Decis Support Wuhan 430200 Hubei Peoples R China

Product recovery is an important business because of its great economic, social, and environmental benefits in practice. In this paper, a location-inventory problem (LIP) in a closed-loop supply chain (CLSC) is investigated to optimize facility location and inventory control decisions by considering product recovery. The objective is to optimize facility location and inventory control decisions to minimize the total cost of business operations in a closed-loop supply chain system. We formulate this problem as a mixed-integer nonlinear programming model and design a modified hybrid differential evolution algorithm (MHDE) to solve it efficiently. Finally, numerical results are presented to validate the performance of the new algorithm. The results show that MHDE is more efficient and effective than Lingo and other algorithms for the research problem under study. Managerial insights are also derived for business managers to improve their supply chain performance.

关键词： Location-inventory problem Closed-loop supply chain mixed integer nonlinear programming Differential evolution Product recovery

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Integrated Optimization of Timetable and Rolling Stock Circulation under mixed Usages of Short-length and Full-length Services in Urban Rail Transit

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Journal of Harbin Institute of Technology(New Series) 2024年第6期31卷 1-15页

作者： Jing Teng Jinke Gao Pengling Wang College of Transportation Engineering Tongji UniversityShanghai 201804China Shanghai Key Laboratory of Rail Infrastructure Durability and System Safety Tongji UniversityShanghai 201804China Shanghai Collaborative Innovation Research Center for Multi-Network&Multi-Modal Rail Transit Tongji UniversityShanghai 201804China

The rapid growth of passenger flow in urban rail transit has led to great service pressures for metro companies in organizing train services to provide higher transportation capacities in order to satisfy passengers' travel demand, especially on those metro lines with insufficient rolling stock. In order to cope with high passenger flow service pressure, a mixed integer nonlinear programming(MINLP) model is proposed to optimize the line plan, timetable and rolling stock circulation simultaneously, to reduce the number of rolling stocks and increase the number of full-length services. A two-step algorithm strategy is proposed. In the first stage, the train timetable is optimized under the assumption that all the train services are the full-length services. In the second stage, the rolling stock plan is optimized based on the timetable optimized in the first stage. To ensure a feasible rolling stock circulation, certain full-length services are shortened to the short-length services due to the limited number of rolling stocks. Numerical experiments are performed based on the real-life data of Shanghai Metro Line 8. Results show that the proposed method can efficiently optimize the timetable and rolling stock circulation of the whole operation day. The optimized results are beneficial for both the service and the operational costs.

关键词： urban rail transit mixed integer nonlinear programming timetable design rolling stock circulation

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A Timetable Optimization Model for Passenger and Freight Transport on Airport Rail Line 23

A Timetable Optimization Model for Passenger and Freight Tra...

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23rd COTA International Conference of Transportation Professionals (CICTP) - Innovation-Empowered Technology for Sustainable, Intelligent, Decarbonized, and Connected Transportation

作者： Wang, Baifan Li, Wenquan Yu, Jingcai Deng, Anxin Southeast Univ Sch Transportat Nanjing Peoples R China Southeast Univ Jiangsu Prov Collaborat Innovat Ctr Modern Urban Nanjing Peoples R China

ISBN: (数字)9780784484869

ISBN: (纸本)9780784484869

The application of urban rail transit systems for fast, efficient, and environment-friendly freight transportation is a rising trend in some countries. This paper addresses an urban freight transportation strategy using surplus capacity resources of the airport rail line to solve the intercity freight transportation problem by inserting dedicated freight trains. First, we develop a hybrid nonlinear programming model to collaboratively optimize passenger and freight train timetables to maximize operating company profits. The model covers the relationship among the participants in the scheduling process, including delivery time, departure intervals, stopping schemes, and train capacity. Then, YALMIP and CPLEX are adopted to find a globally optimal solution after linearizing the model. Finally, the proposed method is demonstrated by the Capital Airport Line in Beijing, China. The results show that the proposed model can provide the potential for addressing various freight demands and increasing the operating company's profits.

关键词： Urban Freight Freight on Transit Airport Line mixed integer nonlinear programming

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Hybrid MPC System for Platoon based Cooperative Lane change Control Using Machine Learning Aided Distributed Optimization

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TRANSPORTATION RESEARCH PART B-METHODOLOGICAL 2022年 159卷 104-142页

作者： Zhang, Hanyu Du, Lili Shen, Jinglai Univ Florida Dept Civil & Coastal Engn Gainesville FL 32608 USA Univ Maryland Dept Math & Stat Baltimore MD 21250 USA

This study is devoted to developing a platoon-based cooperative lane-change control (PB-CLC). It coordinates the trajectories of a CAV platoon under a platoon-centered platooning control to accommodate the CAV lane-change requests from its adjacent lane, aiming to reduce the negative traffic impacts on the platoon resulting from lane-change maneuvers, on the premise of ensuring CAVs' safety and mobility. Mathematically, the PB-CLC control is established using a hybrid model predictive control (MPC) system. The hybrid MPC system involves an MPC-based mixed integer nonlinear programming optimizer (MINLP-MPC) for optimal lane-change decisions, which considers multiple objectives such as traffic smoothness, driving comfort and lane-change response promptness subject to vehicle dynamics and safety constraints. To ensure the feasible lane-change, this study investigates and provides a lower bound of the lane-change time window by analyzing the MINLP-MPC model feasibility. Apart from the optimal lane-change decision consideration, the hybrid MPC system is well designed to ensure the control continuity and smoothness. In particular, the hybrid MPC system control feasibility and stability are proved to enable the platoon's back-and-forth state switchings between car-following and lane-change accommodation states. Next, we developed a machine learning aided distributed branch and bound algorithm (ML-DBB) to solve the MINLP-MPC model within a control sampling time interval (< 1 second). Specifically, built upon computer simulation and the c-LHS sampling technique, supervised machine learning models are developed offline to predict a reduced solution space of the integer variables, which is further integrated into the distributed branch and bound method to solve the MINLP-MPC model efficiently online. Extensive numerical experiments validate the effectiveness and applicability of the ML-DBB algorithm and the PB-CLC control.

关键词： connected and autonomous vehicles cooperative lane-change vehicle platooning model predictive control hybrid system controller mixed integer nonlinear programming supervised machine learning distributed branch and bound

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Joint Task Offloading and Resource Allocation Optimisation for BS-impaired UAV-Assisted Edge Computing 6

Joint Task Offloading and Resource Allocation Optimisation f...

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6th International Conference on Data-Driven Optimization of Complex Systems (DOCS)

作者： Dong, Aofei Hu, Yaowen Mei, Zhixin Feng, Kuiyuan Chongqing Normal Univ Coll Comp & Informat Sci Chongqing Peoples R China

ISBN: (纸本)9798350377859;9798350377842

With the continuous advancement of wireless communication technologies, the negative impact of base station (BS) impairments on network performance is becoming more and more significant. In this paper, we explore how task offloading and resource allocation optimisation can be achieved through Unmanned Aerial Vehicle (UAV)-assisted edge computing in the context of BS impairments. This study proposes a UAV-assisted vehicular edge computing architecture that aims to provide the required Quality of Service (QoS) for computationally intensive and delay-sensitive applications. We provide an in-depth study of the task offloading and resource allocation problem with the aim of maximising the benefit gained by the vehicle by offloading tasks. This benefit is quantified by measuring the weighted sum of task completion time and energy consumption. We are faced with a mixed integer nonlinear programming (MINLP) problem that involves the joint optimisation of the task offloading decision, the uplink transmission power of the mobile vehicle, and the computational resource allocation on the UAV. Given the complexity of the problem, finding an optimal solution is both difficult and unrealistic for large-scale networks. To address this challenge, we employ a decomposition strategy that splits the original problem into two subproblems: a resource allocation (RA) problem that fixes the task offloading decision, and a task offloading (TO) problem that optimises the optimal value function corresponding to the RA problem. We solve the RA problem using convex optimisation and proposed convex optimisation techniques and apply genetic algorithms to solve the TO problem. The results of simulation experiments show that our proposed algorithm is close to the optimal solution in terms of performance and significantly improves the vehicle unloading benefits when compared to the conventional methods. This suggests that UAV-assisted edge computing can effectively optimise task offloading and resou

关键词： base station unmanned aerial vehicle task offloading resource allocation mixed integer nonlinear programming

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On hub location problems in geographically flexible networks

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INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 2022年第4期29卷 2226-2249页

作者： Blanco, Victor Puerto, Justo Univ Granada Inst Math Granada 18011 Spain Univ Seville Inst Math Seville 41012 Spain

In this paper, we propose an extension of the uncapacitated hub location problem where the potential positions of the hubs are not fixed in advance. Instead, they are allowed to belong to a region around an initial discrete set of nodes. We give a general framework in which the collection, transportation, and distribution costs are based on norm-based distances and the hub-activation setup costs depend not only on the location of the hub that are opened but also on the size of the region where they are placed. Two alternative mathematical programming formulations are proposed. The first one is a compact formulation while the second one involves a family of constraints of exponential size that we separate efficiently giving rise to a branch-and-cut algorithm. The results of an extensive computational experience are reported showing the advantages of each of the approaches.

关键词： hub location mixed integer nonlinear programming neighborhoods network design

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Mathematical model for the scheduling of real-time applications in IoT using Dew computing

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JOURNAL OF SUPERCOMPUTING 2022年第5期78卷 7464-7488页

作者： Javadzadeh, Ghazaleh Rahmani, Amir Masoud Kamarposhti, Morteza Saberi Islamic Azad Univ Comp Engn Dept Sci & Res Branch Tehran Iran Natl Yunlin Univ Sci & Technol Future Technol Res Ctr 123 Univ RdSect 3 Touliu 64002 Yunlin Taiwan Islamic Azad Univ Comp Engn Dept South Tehran Branch Tehran Iran

The dew computing paradigm is emerging as a complement of cloud computing to cover its limitations. Independence is one of the essential features of dew computing. It means that it can continue to provide services without an Internet connection. These characteristics of dew computing allow it to find a niche in real-time applications. The importance of real-time applications in daily human life is not hidden due to the growing development of the Internet of Things. In this paper, the hierarchical architecture of cloud-fog-dew is presented to overcome the limitations of cloud computing in real-time applications such as latency and resource management. Also, a mixed integer Non-Linear programming model is presented for the scheduling of real-time applications in the proposed architecture. It aims to reduce power consumption and Internet traffic. Besides, the proposed model is supported by Non-dominated Sorting Genetic Algorithm II to provide scalability. The simulation results demonstrate that completing tasks in the dew computing layer can reduce Internet dependency while also reducing power consumption and traffic. As a result, under the suggested paradigm, the number of tasks missed due to stoppage or Internet disturbance is reduced.

关键词： Internet of Things Fog computing GAMS Dew computing Scheduling mixed integer nonlinear programming NSGA-II

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