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An algorithm with exact bounds for coverage path planning in UAV-based search and rescue under windy conditions

COMPUTERS & OPERATIONS RESEARCH 2025年 173卷

作者： Kazemdehbashi, Sina Liu, Yanchao Wayne State Univ Dept Ind & Syst Engn 4815 4th St Detroit MI 48201 USA

Unmanned aerial vehicles (UAVs) are increasingly utilized in global search and rescue efforts, enhancing operational efficiency. In these missions, a coordinated swarm of UAVs is deployed to efficiently cover expansive areas by capturing and analyzing aerial imagery and footage. Rapid coverage is paramount in these scenarios, as swift discovery can mean the difference between life and death for those in peril. This paper focuses on planning the flight paths for multiple UAVs in windy conditions to efficiently cover rectangular search areas in minimal time. We address this challenge by dividing the search area into a grid network and formulating it as a mixed-integer program (MIP). We derive a precise lower bound for the objective function and develop a fast algorithm with a proven capability of finding either the optimal solution or a near-optimal solution with a constant absolute gap to optimality. Notably, as the problem complexity increases, our solution exhibits a diminishing relative optimality gap while maintaining negligible computational costs compared to the MIP approach. The fast execution speed of the algorithms is demonstrated by numerical experiments with area sizes up to 10,000 grid cells.

关键词： Coverage path planning Unmanned aerial vehicle mixed-integer programming

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Reliability improvement of rolling stock planning with maintenance requirements for high-speed railway

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RELIABILITY ENGINEERING & SYSTEM SAFETY 2025年 259卷

作者： Niu, Jiaxin Qiao, Ke Zhao, Peng Beijing Jiaotong Univ Sch Traff & Transportat Beijing 100044 Peoples R China

The rolling stock planning problem is a key step in the high-speed railway transit planning process. When trip delays, railway departments may need to incur considerable additional costs for plan adjustments to quickly resume operations. Therefore, we consider the impact of trip delay probabilities during rolling stock planning, aiming to minimise the total travel cost and maximise plan robustness to enhance the reliability of plan execution. A space-time-state network is established to describe the operation of rolling stocks considering accumulated mileage and running time constraints for maintenance, representing the rolling stock planning problem as a mixed-integer nonlinear programming model. Then, an alternating direction method of multipliers (ADMM)-based decomposition mechanism that decomposes the model into a set of rolling stock route selection subproblems is introduced, where each subproblem is efficiently solved by a maintenance-constrained shortest path algorithm related to reliability. A set of different scale real-life cases based on trips managed by a depot in China are used to verify the effectiveness of the proposed model and algorithm. The results show that the ADMM considerably outperforms the traditional Lagrangian relaxation (LR) method. On a set of larger-scale cases, the proposed ADMM with enhancements obtains an optimality gap of 2.42 % on average. This result is substantially better than LR, which provides optimality gaps of 32.55% on average. Finally, the model in this paper effectively enhances the probability of successful rolling stock route execution in trip delay scenarios, resulting in a rolling stock plan with improved reliability.

关键词： High-speed railway Rolling stock planning Reliability plan mixed-integer programming ADMM

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A mixed-integer PDE-constrained optimization formulation for constructing electromagnetic cloaks with multiple materials

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COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 2025年第2期90卷 337-360页

作者： Vogt, Ryan H. Leyffer, Sven Munson, Todd Natl Secur Agcy Math & Comp Sci Div 9800 Savage Rd Ft George G Meade MD 20755 USA Argonne Natl Lab Math & Comp Sci Div 9700 S Cass Ave Lemont IL 60439 USA

We study the design of an electromagnetic cloak from multiple materials with an additional constraint on the mass of the cloak. Our problem is an example of a topology optimization problem, and we formulate this problem as a mixed-integer partial-differential equation constrained optimization (MIPDECO) problem, where Maxwell's equation models the propagation of the wave through the cloak and surrounding medium. We use binary variables to model the assignment of the different materials, and their relevant properties (permittivity and density). The mass constraint adds a nontrivial constraint to this problem. We propose a two-phase strategy to solve this problem. In the first phase, we solve a continuous relaxation, and then propose a new variant of the feasibility pump that exploits the structure of the PDE to obtain an initial integral solution candidate. In the second phase, we use a trust-region approach to improve this incumbent. We also consider a continuation or mesh-sequencing approach to find better solutions faster on consecutively finer meshes. We present detailed numerical results to illustrate the effectiveness of our approaches for constructing multi-material cloaks with a mass constraint.

关键词： Topology optimization PDE-constrained optimization mixed-integer programming Nonlinear optimization

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An Agile Mobilizing Framework for V2G-Enabled Electric Vehicles Under Wildfire Risk

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2025年第4期74卷 5771-5783页

作者： Bayani, Reza Manshadi, Saeed Univ Calif San Diego La Jolla CA 92093 USA San Diego State Univ San Diego CA 92182 USA

Public safety power shut-offs (PSPSs), implemented by California utilities during high wildfire risk periods, lead to the de-energization of grid sections and leave certain customers out of power for several hours and even days. We propose an agile decision support system (DSS) to mitigate these impacts by harnessing electric vehicles (EVs) as mobile energy sources serving the multiple microgrids ($\mu$Gs) formed within affected communities. Given that not all $\mu$Gs possess adequate energy storage and distributed energy resources (DERs), we advocate for the mobilization of vehicle-to-grid (V2G)-enabled EVs for equitable and resilient energy access. Our emergency service relocation (ESR) model incentivizes EV owners to transport stored energy between $\mu$Gs. However, traditional DSS cannot promptly solve the associated mixed-integer programming (MIP) problem, necessitating a faster solution algorithm for rapid EV deployment under emergency conditions. We introduce a learning framework employing graph convolutional networks (GCNs) that significantly expedites the MIP problem's solution by predicting binary values. Our results demonstrate the effectiveness of the proposed framework in promoting grid resilience and considerably reducing solve time when the problem has 69k binary decision variables.

关键词： Wildfires Vehicle-to-grid Power systems Mathematical models Resilience Planning Power system dynamics Prediction algorithms Vehicle dynamics Transportation Electric vehicle resilience microgrid mixed-integer programming graph convolutional networks

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Strategic workforce and project planning for engineering automotive production systems: tackling the transition to electric vehicles

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2025年第3期63卷 1105-1125页

作者： Kolter, Maximilian Grunow, Martin Kolisch, Rainer Stablein, Thomas Tech Univ Munich TUM Sch Management Dept Operat & Technol Arcisstr 21 Munich Germany Mercedes Benz AG Sindelfingen Germany

Car manufacturers are electrifying their product portfolios as a reaction to restrictions imposed on car emissions. This leads to additional product introductions of battery electric vehicles to the existing portfolio of internal combustion engine vehicles. For each introduction, car manufacturers must engineer the corresponding production systems. The engineering of these production systems is executed as projects that consist of designing, building, installing, and testing, requiring different types of engineers. Car manufacturers deploy an engineering workforce and outsource work to engineering service providers. In practice, workforce planning, project planning, and outsourcing are performed sequentially using spreadsheets. However, portfolio electrification increases the complexity of planning, calling for more advanced methods. We formulate an integrated workforce and project planning problem (mixed-integer programme) to minimise outsourcing and perform an experimental study using realistic data representing different prevalent strategies for portfolio electrification. Our approach significantly reduces outsourcing and increases workforce utilisation compared to current industry practice for a wide range of workforce sizes. Furthermore, we investigate the benefit of partially aligning the current practice with our integrated approach. Optimising outsourcing alone while maintaining the sequential planning process reaps 70% to 80% of the potential benefits, and integrating workforce or project planning achieves up to 90%.

关键词： Automotive industry production systems workforce planning project scheduling mixed-integer programming

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Planning an airport shuttle network with air taxis using choice-based optimization

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OR SPECTRUM 2025年 1-35页

作者： Hagspihl, Thomas Kolisch, Rainer Schiffels, Sebastian Tech Univ Munich TUM Sch Management Arcisstr 21 D-80333 Munich Germany Univ Augsburg Inst Business Adm Univ Str 16 D-86159 Augsburg Germany

Airports and airlines share a common interest in providing passengers with fast and convenient access to airports. With the introduction of air taxis as a new means of transport, the opportunity will soon emerge to introduce air taxi shuttle services to airports. In this context, for each individual airport the question arises where the facilities for landing, ground handling and take-off, also called vertiports, should be located in the area surrounding the airport. We formulate the problem as a hub location problem with multiple allocation, with the objective to maximize the number of passengers who choose to reach the airport by air taxi. In our model, we explicitly incorporate passengers' choice behavior with respect to available means of transport using a multinomial logit model. We linearize the problem and provide guidance on the steps needed to use the model in practice. In an extensive case study, we apply the model to real data for Munich Airport, perform a stated preference study to parameterize the multinomial logit model, suggest locations for vertiports throughout Bavaria as a result, and investigate to what extent the introduction of air taxi shuttle flights can reduce travel times to Munich Airport.

关键词： Transportation Advanced air mobility eVTOL Airport operations mixed-integer programming Discrete choice modeling

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The flex-route transit planning problem with meeting points

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2025年 195卷

作者： Li, Mingyang Wu, Lingxiao Wang, Yadong Tang, Jinjun Feng, Tao Cent South Univ Sch Traff & Transportat Engn Smart Transportat Key Lab Hunan Prov Changsha 410075 Peoples R China Hong Kong Polytech Univ Dept Aeronaut & Aviat Engn Hong Kong Peoples R China Nanjing Univ Sci & Technol Sch Econ & Management Nanjing 210094 Peoples R China Hong Kong Polytech Univ Fac Business Dept Logist & Maritime Studies Hong Kong Peoples R China

As an innovative alternative to ridesharing, flex-route transit (FRT) is widely acknowledged as a promising solution, especially in scenarios in which transportation demand is low or dispersed. This paper addresses the FRT planning problem with meeting points (FRTPP-MP), which conceptualizes each passenger's pick-up/drop-off request as a set of points (i.e., a cluster) containing the designated pick-up/drop-off point and alternative points (i.e., meeting points), stipulating that only one point in each cluster needs to be visited to fulfill the request. The aim is to minimize both the travel cost of vehicles and the walking cost of passengers by simultaneously optimizing the routes of vehicles and the selection of nodes within their respective clusters. We formulate the FRTPP-MP as a mixed-integer programming (MIP) model and develop an exact branch-and-price (BAP) algorithm to solve it. To tackle the specific challenges of cluster visit restrictions in the pricing problem, we design a tailored bidirectional label correction algorithm (TBLCA), which is further enhanced by a novel acceleration strategy. Extensive computational experiments are conducted based on benchmark instances generated from a real-life FRT system. The numerical results highlight our solution algorithm's satisfactory performance. Furthermore, managerial insights from a sensitivity analysis suggest that introducing meeting points can substantially reduce the costs associated with FRT.

关键词： Flex-route transit service Transit planning Meeting points mixed-integer programming Branch-and-price

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Robust fuzzy programming for designing a closed-loop supply chain under uncertainty and flexible constraints

CLEANER LOGISTICS AND SUPPLY CHAIN

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CLEANER LOGISTICS AND SUPPLY CHAIN 2025年 14卷

作者： Dehshiri, Seyyed Jalaladdin Hosseini Amiri, Maghsoud Allameh Tabatabai Univ Fac Management & Accounting Dept Ind Management Tehran Iran

Due to enacting laws and increasing awareness of environmental issues, the design of a Closed-Loop Supply Chain network (CLSC) has received attention. The design of CLSC is a strategic issue with long-term effects and faces uncertainty in the real world, which affects its performance. In the studies on CLSC, robust optimization, cognitive uncertainty, and soft constraints are not assessed simultaneously in modeling and this area is deficient. So, in this investigation, mixed-robust-possibilistic-flexible programming is proposed. This research develops CLSC problem-solving approaches under conditions of cognitive uncertainty and soft constraints and leads to the presentation of operation engineering and optimization in CLSC. The Decision Maker's (DM) risk level is measured flexibly using a credibility criterion. Also, deviation of possibilistic and constraint violations are controlled in the proposed approach. To evaluate the presented approach, a study is executed to design a paper supply chain with economic and environmental objectives. The results show that it is possible to determine the number, place of facilities, and optimal flow of products and materials between different centers. The proposed approach and multi-objective model solution method are capable of providing realistic and flexible solutions based on the trade-off between other objectives and DMs' preferences. The performance of the proposed approach was analyzed and results confirmed the developed approach compared to similar approaches for the design of CLSC.

关键词： Closed-loop supply chain Chance-constrained programming mixed-integer programming Flexible approach Possibilistic absolute deviation

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Optimizing air traffic management through point merge procedures: Minimizing delays and environmental impact in arrival operations

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JOURNAL OF AIR TRANSPORT MANAGEMENT 2025年 123卷

作者： Hardell, Henrik Otero, Evelyn Polishchuk, Tatiana Smetanova, Lucie Linkoping Univ LiU Commun & Transport Syst S-60174 Norrkoping Sweden Luftfartsverket LFV Airspace Unit S-60179 Norrkoping Sweden Royal Inst Technol KTH Dept Engn Mech S-10044 Stockholm Sweden

We present an application of a mixed-integer programming (MIP) framework for automatic traffic synchronization, providing safe separation between the arriving traffic within the terminal maneuvering area (TMA) of an airport implementing point merge (PM) procedures. Additionally, the proposed methodology ensures conflict-free operations when departures and arrivals share a common runway. Based on real traffic scenarios for two European airports, we model realistic descent profiles and assume all the arrivals are performing the most fuel-efficient continuous descent operations (CDOs). We compare two scenarios: in the first, the arriving aircraft are strictly forced to adhere to the published arrival route structures, meaning that a turn towards the merge point may not be initiated prior to reaching the point merge system (PMS), while in the second scenario, aircraft maybe assigned a shortcut from a published waypoint along the arrival route. We evaluate the resulting arrival flight efficiency and compare it to that of the actual flights, arriving during the hour selected for our optimization, noticing varying benefits for the two airports and whether shortcuts are allowed or not. Given the correct setting for the specific airport, we demonstrate that our approach provides significant benefits, including increased vertical performance as well as reduced time and distance, contributing to lower levels of noise and fuel savings, accompanied by reduced emissions.

关键词： Point merge Arrival optimization TMA operations mixed-integer programming

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A bi-objective mixed-integer non-linear programming model with Grasshopper Optimization Algorithm for military-based humanitarian supply chains

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Decision Analytics Journal 2024年 10卷

作者： Aghsami, Amir Sharififar, Simintaj Moghaddam, Nader Markazi Hazrati, Ebrahim Jolai, Fariborz School of Industrial and Systems Engineering College of Engineering University of Tehran P.O. Box 11155-4563 Tehran Iran School of Industrial Engineering K.N. Toosi University of Technology (KNTU) Tehran Iran Department of Health in Disasters and Emergencies School of Nursing AJA University of Medical Sciences Tehran Iran Critical Care Quality Improvement Research Center Shahid Modarres Hospital Shahid Beheshti University of Medical Sciences Tehran Iran Department of Health Management and Economics Faculty of Medicine AJA University of Medical Sciences Tehran Iran Trauma Research Center. Aja University of Medical Sciences Tehran Iran

Military systems have many components, such as garrisons, border guards, and industries with a large population that may be affected by disasters. Garrisons, hospitals, clinics, and other facilities in military systems are needed to reduce human casualties. However, these facilities may not have enough resources to handle the disruption. There is no mathematical model to manage disasters with military systems including garrisons and border guards as relief forces interacting with non-military medical centers. This study develops a model for coordinating humanitarian supply chains and logistics within the military system. The affected military sites (AMSs) are military hospitals, clinics, industries, airports, military organizational settlements, garrisons, and border guards. A bi-objective mixed integer non-linear programming model is developed to minimize total costs during pre- and post-disaster planning, a weighted average of injury time in military vehicles, and total delay in relief items (RIs) distribution and rescue operations. For small and medium test problems, GAMS software is used, and for large test problems, the Grasshopper Optimization Algorithm (GOA) is proposed. We conducted some numerical examples to demonstrate the proposed model's efficiency and feasibility and evaluate the metaheuristic. Sensitivity analyses are conducted to evaluate model behavior under various conditions. © 2024 The Authors

关键词： Bi-objective model Disaster management Grasshopper optimization Humanitarian supply chain Military logistics system mixed-integer programming

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