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A MINP model and hybrid heuristic algorithm for railway cold chain service network design problem: a case study of China

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2025年第1期63卷 171-192页

作者： Li, Dandan Gan, Mi Qiao, Yu Ou, Qichen Liu, Xiaobo Southwest Jiaotong Univ Sch Transportat & Logist Chengdu Peoples R China Southwest Jiaotong Univ Natl Engn Lab Integrated Transportat Big Data Appl Chengdu Peoples R China Southwest Jiaotong Univ 111 Erhuanlu Beiyiduan Chengdu 610031 Sichuan Peoples R China

Railway Cold Chain Service Network Design (RCC-SND) aims to optimise resource allocation and utilisation to ensure the efficient transportation of perishable foods. In this study, we propose a mixed integer nonlinear programming (MINP) model to solve the hub selection, service frequency determination, wagon flow organisation and routing problems in RCC-SND. The application of the model is illustrated using the real network comprising 163 cities in China. The PSO-GA algorithm is proven effective in solving the problem. Furthermore, we introduce two future scenarios to assess the carbon reduction potential and economic costs of railway cold chain operations. There are some main findings: as the hub number increases from 30 to 40, the total cost decreases, as the hub continues to rise, this reduction is offset by the increased hub operational costs. Increasing hubs can enhance direct train frequency while causing railway capacity redundancy, this redundancy can be addressed by freight volume increase, as demonstrated in this study, 4.5 times increase in freight volume can boost train utilisation by up to 12.5%. By 2030, railway cold chain carbon emissions are projected to exceed 1.1 million tons, the adoption of hydrogen as alternative energy is an economically viable solution for emission reduction.

关键词： Perishable food industry railway cold chain transportation hub-routing problem mixed integer nonlinear programming SDG 9: Industry innovation and infrastructure

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A QoE and Availability-Aware Framework for Network Slice Placement and Resource Allocation

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IEEE ACCESS 2025年 13卷 1481-1495页

作者： Dobreff, Gergely Bader, Attila Pasic, Alija Budapest Univ Technol & Econ Fac Elect Engn & Informat Dept Telecommun & Artificial Intelligence H-1111 Budapest Hungary Ericsson Hungary H-1117 Budapest Hungary

In 5G networks, the deployment of network slices enabled by Software-Defined Networking (SDN) is becoming a critical component for delivering tailored services to meet diverse application needs. However, this introduces challenges in network management, particularly in efficiently allocating resources to ensure that each network slice meets its specific Quality of Service (QoS) and availability requirements. Simultaneously, it must optimize overall network performance and network operator's profit, which is linked to the Quality of Experience (QoE) of the end-users. Existing works offer either an availability-based solution or a QoE-aware solution to this problem, but not both. This paper addresses the end-to-end network slice resource allocation problem by simultaneously considering QoS and availability requirements in slice placement, while employing a QoE-aware strategy for resource allocation. We propose a framework that optimizes the network operator profit i.e. the highest QoE with the least resource usage, and can be flexibly configured to model realistic scenarios. Arbitrary network slice requirements can be defined using slice-specific QoS/QoE mapping, resource requirements, end-to-end latency and availability. For solving the formulated problem a mixed integer nonlinear programming (MINLP) formulation and efficient heuristic methods are proposed. Our solution accounts for the non-linear QoS/QoE relationship, utilizes redundantly placed Service Function Chains (SFCs) to increase availability, and supports the sharing of Virtual Network Functions (VNFs) among SFCs to optimize resource usage. Through extensive simulations on realistic network topologies and slice requests, we demonstrate the framework's effectiveness in offering flexible and efficient network slice placement and resource allocation, utilizing a baseline heuristic from related studies. The results indicate that while the exact method delivers an optimal solution, heuristic approaches are suita

关键词： Quality of experience Resource management Quality of service Substrates Telecommunication network reliability Network slicing Virtual links Measurement Bandwidth Telecommunications Availability mixed integer nonlinear programming E2E network slicing placement quality of experience (QoE) quality of service (QoS) resource allocation service function chaining (SFC)

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Integrated train timetable with supply-demand interactions at the Chinese high-speed railway

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OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE 2025年 131卷

作者： Yuan, Jiawei Gao, Yuan Ke, Jiannan Yang, Lin Beijing Inst Technol Sch Management Beijing 100081 Peoples R China Beijing Inst Technol Digital Econ & Policy Intelligentizat Key Lab Mini Beijing 100081 Peoples R China Beijing Inst Technol Jiaxing Key Lab Digital Econ & Data Operat Yangtze Delta Reg Acad Jiaxing 314019 Peoples R China Wuhan Univ Sch Econ & Management Wuhan 430072 Peoples R China Chinese Univ Hong Kong Sch Data Sci Shenzhen 518172 Peoples R China

In traditional Chinese railway operations, train timetable and unit assignment are usually separated from pricing and seat allocation, resulting in a decrease in revenue and an increase in operating costs. In this paper, we study the integrated problem of train timetable, unit assignment, pricing, and seat allocation, where passenger choice behavior is modeled by the multinomial logit (MNL) model. This integration enables us to explicitly capture supply-demand interactions. The problem is formulated as a mixed integer nonlinear programming model with the objective of maximizing total profit. By converting the MNL model into its equivalent convex form, we recast the model as a tractable reformulation, allowing the use of a general-purpose solver to solve practical-sized instances. Based on real data from high-speed railway lines in China, three sets of case studies are conducted to validate the effectiveness and efficiency of the proposed approach.

关键词： Train timetable Pricing Passenger choice mixed integer nonlinear programming

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Optimal and Adaptive Operation of a Hydropower System with Unit Commitment and Water Quality Constraints

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WATER RESOURCES MANAGEMENT 2012年第3期26卷 707-732页

作者： Ferreira, Andre R. Teegavarapu, Ramesh S. V. Florida Atlantic Univ Dept Civil Environm & Geomat Engn Boca Raton FL 33431 USA

Management of water resources has become more complex in recent years as a result of changing attitudes towards sustainability and the attribution of greater attention to environmental issues, especially under a scenario of water scarcity risk introduced by climate changes and anthropogenic pressures. This study addresses the optimal short-term operation of a multi-purpose hydropower system under an environment where objectives are conflicting. New optimization models using mixed integer nonlinear programming (MINLP) with binary variables adopted for incorporating unit commitment constraints and adaptive real-time operations are developed and applied to a real life hydropower reservoir in Brazil, utilizing evolutionary algorithms. These formulations address water quality concerns downstream of the reservoir and optimal operations for power generation in an integrated manner and deal with uncertain future flows due to climate change. Results obtained using genetic algorithm (GA) solvers were superior to gradient based methods, converging to superior optimal solutions especially due to computational intractability problems associated with combinatorial domain of integer variables in the unit commitment formulation. The adaptive operation formulation in conjunction with the solution of turbine unit commitment problem yielded more reliable solutions, reducing forecasting uncertainty and providing more flexible operational rules.

关键词： Hydroelectric power generation mixed integer nonlinear programming Optimization Unit commitment Adaptive operation Water quality Genetic algorithms

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A multi-level vehicle-to-grid optimal scheduling approach with EV economic dispatching model

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ENERGY REPORTS 2021年 7卷 22-37页

作者： Guo, Song Qiu, Zejing Xiao, Chupeng Liao, Hui Huang, Yuping Lei, Ting Wu, Dan Jiang, Qian Nari Grp Corp State Grid Elect Power Res Inst Luoyu Rd 134 Wuhan 430074 Peoples R China Wuhan Efficiency Evaluat Co Ltd State Grid Elect Power Res Inst Wuhan 430074 Peoples R China Chinese Acad Sci Guangzhou Inst Energy Convers Nengyuan Rd 2 Guangzhou 510640 Peoples R China State Grid Shanghai Elect Power Co Yuanshen Rd 1122 Shanghai 201204 Peoples R China

As electric vehicles (EVs) are eco-friendly and have the feature of flexible power storage, the electric vehicle development is strongly supported by many governments. The market share of EVs has been rising steadily in recent years to promote the long-term growth of the available EV battery resources to participate in vehicle to grid (V2G). When a large number of electric vehicles can connect to grids randomly for charging or discharging, this inevitably brings large load fluctuation in regions and new challenges to the operation scheduling and control of power systems. Therefore, this paper proposed a new multi-level optimal V2G scheduling approach, ensuring the smooth operation and control from the V2G control center to the EV users. This paper also introduced a new EV economic dispatch optimization model to minimize the operating costs of regional V2G systems. A case analysis of the IEEE 33-bus system with 100 EVs verified the feasibility of the proposed model and indicated that the proper size control of total EV battery capacities with ramp adjustment can reduce additional load fluctuations caused by large-scale vehicles to grid. Moreover, the multi-stage TOU pricing mode is another effective measures that can trigger a next round of EV charging and discharging service. (C) 2021 The Authors. Published by Elsevier Ltd.

关键词： Electric vehicle V2G operation Multi-level scheduling approach EV economic dispatching mixed integer nonlinear programming

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Critical Traffic Control Locations for Emergency Evacuation

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JOURNAL OF TRANSPORTATION ENGINEERING 2013年第10期139卷 1030-1038页

作者： Zhang, Xiongfei He, Rachel Shi, Qixin Ban, Jeff Ran, Bin Shenzhen Univ Coll Rail Transportat Shenzhen Key Lab Urban Rail Transit Shenzhen 518060 Peoples R China Santa Clara Univ Dept Civil Engn Santa Clara CA 95053 USA Tsinghua Univ Dept Civil Engn Beijing 100084 Peoples R China Rensselaer Polytech Inst Dept Civil & Environm Engn Troy NY 12180 USA Univ Wisconsin Dept Civil & Environm Engn Madison WI 53706 USA

Proper traffic control and guidance are imperative to reduce fatalities and property damage. When resources are scarce during emergency evacuation for any natural or artificial disasters, it is crucial to identify the most critical traffic control locations or intersections to deploy temporary control devices or to arrange manual traffic guidance so that the best system performance can be achieved. To answer the urgent theoretical and practical deployment problems, this study has proposed mixed integer nonlinear programming (MINLP) models for both static and dynamic situations. The proposed models aim to find the most crucial intersections, the optimal traffic control strategies for those intersections, and the best destination choices for evacuees to minimize the total system cost. The proposed models assume that evacuees will follow their past travel experience to safe zones unless they encounter the critical intersections. At those fully controlled critical intersections, evacuees will completely comply with the evacuation guidance to help achieve the minimum total system cost. The proposed MINLP models have also been expanded to include cell-based modules to capture the dynamic nature of evacuation flows, which is essential for real-time operation. Numerical tests on a large network with multiple origins and destinations have shown that the proposed models perform reasonably well.

关键词： User equilibrium Emergency evacuation mixed integer nonlinear programming Dynamic traffic assignment Cell transmission model System optimal

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OPTIMIZATION STRATEGIES FOR THE VULNERABILITY ANALYSIS OF THE ELECTRIC POWER GRID

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SIAM JOURNAL ON OPTIMIZATION 2010年第4期20卷 1786-1810页

作者： Pinar, Ali Meza, Juan Donde, Vaibhav Lesieutre, Bernard Sandia Natl Labs Dept Informat & Decis Sci Livermore CA 94550 USA Univ Calif Berkeley Lawrence Berkeley Lab High Performance Comp Res Dept Berkeley CA 94720 USA ABB Inc Corp Res Ctr Raleigh NC 27606 USA Univ Calif Berkeley Lawrence Berkeley Lab Environm Energy Technol Div Berkeley CA 94720 USA Univ Wisconsin Dept Elect & Comp Engn Madison WI 53706 USA

Identifying small groups of lines, whose removal would cause a severe blackout, is critical for the secure operation of the electric power grid. We show how power grid vulnerability analysis can be studied as a bilevel mixed integer nonlinear programming problem. Our analysis reveals a special structure in the formulation that can be exploited to avoid nonlinearity and approximate the original problem as a pure combinatorial problem. The key new observation behind our analysis is the correspondence between the Jacobian matrix (a representation of the feasibility boundary of the equations that describe the flow of power in the network) and the Laplacian matrix in spectral graph theory (a representation of the graph of the power grid). The reduced combinatorial problem is known as the network inhibition problem, for which we present a mixed integer linear programming formulation. Our experiments on benchmark power grids show that the reduced combinatorial model provides an accurate approximation, to enable vulnerability analyses of real-sized problems with more than 16,520 power lines.

关键词： mixed integer nonlinear programming network inhibition network flow mixed integer linear programming electric power flow network vulnerability graph theory

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A train dispatching model in case of segment blockages by integrating the prediction of delay propagation

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NEURAL COMPUTING & APPLICATIONS 2024年第7期36卷 3595-3611页

作者： Yang, Han Hu, Wenfeng Ma, Shan Peng, Tao Cent South Univ Sch Automat Changsha Peoples R China

In the high-speed railway system, trains' original timetable is often disturbed by some emergencies including geological disasters and equipment failures, which brings great influence to passengers. This paper proposes a real-time high-speed train dispatching model in case of segment blockages, where a railway network is considered. The model includes the following two parts. First, if the trains are not cancelled or decelerated after a blockage occurs, the scope of the affected trains and stations is roughly estimated via the prediction of delay propagation model. Second, with the overall delay as the objective function, this paper constructs a mixed integer nonlinear programming (MINLP) model by considering the following three adjustment strategies: cancellation, delayed departure and deceleration, where the safe headway of the train operation is guaranteed by the moving blocking principle. Furthermore, to reduce the computation complexity, the solution of the model is only considered within the scope obtained in the first stage. The model is verified by using a small railway network with Nanjing as the hub station, which shows that the model is useful for reducing the effect of a disruption on original timetable, especially in comparison with the First Scheduled First Served (FSFS) rule used in practice.

关键词： High-speed train dispatching Delay propagation Train deceleration mixed integer nonlinear programming

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Multi-objective Optimization-Tool for the Universal Application in Chemical Process Design

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CHEMICAL ENGINEERING & TECHNOLOGY 2017年第10期40卷 1867-1875页

作者： Ernst, Philipp Zimmermann, Kristina Fieg, Georg Hamburg Univ Technol Inst Proc & Plant Engn Schwarzenberg Campus 4 D-21073 Hamburg Germany

A universally applicable procedure for multi-objective optimization of chemical processes is developed. A set of known methods and procedures is adapted, combined with newly developed concepts, and integrated into the developed optimization tool, namely, the Adv:ProcessOptimizer. It allows for efficient, comfortable, and robust optimization of a process which is modeled in one of the various linked commercial simulation tools. As a result, the application of the process design with an overlaid optimization is easily accessible for academia and process industry. The industrial styrene process was optimized in order to validate the method. The results show a very densely and mostly equally crowded Pareto front and considerable savings in investment as well as operating costs compared to two reference designs.

关键词： Chemical process design Genetic algorithm mixed integer nonlinear programming Multi-objective optimization

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mixed integer least squares optimization for flight and maintenance planning of mission aircraft

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NAVAL RESEARCH LOGISTICS 2012年第3-4期59卷 212-229页

作者： Kozanidis, George Gavranis, Andreas Kostarelou, Eftychia Univ Thessaly Dept Mech Engn Syst Optimizat Lab Volos Greece Hellen AF Combat Wing 111 N Aghialos Greece

We address the problem of generating a joint flight and maintenance plan for a unit of mission aircraft. The objective is to establish a balanced allocation of the flight load and the maintenance capacity to the individual aircraft of the unit, so that its long-term availability is kept at a high and steady level. We propose a mixed integer nonlinear model to formulate the problem, the objective function of which minimizes a least squares index expressing the total deviation of the individual aircraft flight and maintenance times from their corresponding target values. Using the model's special structure and properties, we develop an exact search algorithm for its solution. We analyze the computational complexity of this algorithm, and we present computational results comparing its performance against that of a commercial optimization package. Besides demonstrating the superiority of the proposed algorithm, these results reveal that the total computational effort required for the solution of the problem depends mainly on two crucial parameters: the size of the unit (i.e., the number of aircraft that comprise it) and the space capacity of the maintenance station. (c) 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012

关键词： fleet availability flight and maintenance planning mission aircraft mixed integer nonlinear programming least squares optimization

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