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Graph-Based Genetic Algorithm for Localization of Multiple Existing Leakages in Water Distribution Networks

JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT 2025年第1期151卷

作者： Oberascher, Martin Minaei, Amin Sitzenfrei, Robert Univ Innsbruck Dept Infrastruct Engn Unit Environm Engn Tech Str 13 A-6020 Innsbruck Austria

Water utility operators prioritize timely repairs of leakages, an activity that refers to a challenging task by the spatial localization of multiple existing leakages within a water distribution network (WDN). In the literature, genetic algorithms (GAs) are applied to find the best combinations of leakages, typically in combination with a reduced number of candidate leakage nodes to reduce computational effort. To address this limitation, a graph-based GA is proposed in this work by considering the topological relationship between the leakage candidate nodes and sizes for the creation of the offspring. In greater detail, each gene in the graph-based GA consists of a leakage place and leakage size, and two random genes are selected based on the roulette wheel selection for the creation of the offspring. Afterward, possible offspring nodes are selected within the shortest path between these two leakage places or in spatial proximity connected to the shortest path, where the leakage size is set to a random value between the leakage sizes of the two genes. The developed approach was tested on part of a WDN with 100 different leakage scenarios and varying number of leakages, sizes, and locations. As the results showed, the graph-based GA significantly improved leakage localization compared with a classic GA and linear programming solver, with a median distance of 44 m between suspected and actual leakage locations given perfect conditions while also being computationally efficient. However, the achievable performance was strongly affected by measurement errors, model uncertainties, and partially unknown nodal demands and was more accurate for localizing leakage places near exactly measured locations and with larger leakage sizes.

关键词： Leakage localization mixed integer linear programming Optimization Parameter uncertainty Water distribution network (WDN)

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Order acceptance and scheduling under eligibility, availability, and budget constraints in distributed heterogeneous flow shop production

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EXPERT SYSTEMS WITH APPLICATIONS 2025年 280卷

作者： Xiong, Fuli Jing, Lin Xiang, Chengfei Han, Yitong Xian Univ Architecture & Technol Sch Informat & Control Engn Xian 710055 Peoples R China

The distributed manufacturing model enhances production flexibility and efficiency. This study investigates the order acceptance and scheduling problem in distributed heterogeneous factories while considering constraints including order-to-factory eligibility, processing time availability, and budget limitations, with the objective of maximizing total profit. The problem involves four interrelated decisions: order selection, allocation, sequencing, and scheduling. To address this, we formulate a Manne-based mixed-integer linear programming (MILP) model and a constraint programming (CP) model. However, these methods become computationally impractical for large instances. To improve efficiency, we develop three logic-based Benders decomposition (LBBD) algorithms that iteratively solve a master problem (MP) for order acceptance and allocation and subproblems (SPs) for scheduling within each factory. A local search (LS) algorithm is integrated to enhance solution quality and convergence speed. Experimental results validate the effectiveness of the proposed approach. For small-scale instances, our method achieves optimality where MILP and CP fail. In large-scale cases, it reduces the optimality gap by 54.2% and 100% across two scenarios while cutting solution time by 20.6%, 84.2%, and 98.3% in three scenarios. Applied to real-world scenarios, it increases total profit by 4.9%, confirming its practical value. These results demonstrate that the proposed LBBD framework significantly outperforms MILP and CP, solving larger instances efficiently with superior solution quality. Additionally, sensitivity analysis highlights key trade-offs in due date flexibility, budget constraints, and order distribution for optimizing scheduling performance.

关键词： Order acceptance and scheduling Logic-based Benders decomposition Constraint programming mixed integer linear programming Local search

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Collaborative optimization of battery electric bus scheduling and charging considering arterial signal coordination under connected environment

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APPLIED ENERGY 2025年 394卷

作者： Yang, Chengcheng Jin, Sheng Gao, Kun Rong, Donglei Bai, Congcong Gao, Xi Shen, Xinyi Yao, Wenbin Jeremie, Adje Alagbe Zhejiang Univ Inst Intelligent Transportat Syst Coll Civil Engn & Architecture Hangzhou 310058 Peoples R China Chalmers Univ Technol Dept Architecture & Civil Engn S-41296 Gothenburg Sweden Zhejiang Univ Zhongyuan Inst Zhengzhou 450000 Peoples R China Zhejiang Univ Polytech Inst Hangzhou 310058 Peoples R China Hong Kong Polytech Univ Dept Ind & Syst Engn Hong Kong 999077 Peoples R China Zhejiang Sci Tech Univ Sch Civil Engn & Architecture Hangzhou 310018 Peoples R China

As a strategic pathway to decarbonization, electrification provides an effective solution for achieving low or even net-zero carbon emissions in transportation systems. Static wireless charging (SWC) presents a promising charging strategy by utilizing the dwell time of battery electric buses (BEBs) at bus stations. This approach can effectively mitigate operational challenges such as limited range and prolonged charging times for connectedbattery electric buses (C-BEBs). This study proposes a collaborative optimization model for C-BEB scheduling and charging considering arterial coordination under connected environment. The model uses mixed integer linear programming (MILP) to develop an arterial signal coordination control approach that considers the operation efficiency of regular vehicles (RVs) and the constraints that C-BEBs passing through signalized intersection without stopping. Additionally, a collaborative optimization model for bus scheduling and charging is constructed, which considers bus headway, bunching, passenger demand, non-stop constraints for C-BEBs, and speed and stop duration limits. This model can enable C-BEBs to flexibly adjust stop time for wireless static charging while maintaining good operational efficiency and planning. Simulation experiment based on real bus lines in Hangzhou shows that the proposed model can charge buses that lack power during operation with almost no impact on overall efficiency. This not only enhances the operational stability of the bus system but also reduces the need for additional backup buses prepared for situations where buses terminate mid-route due to power shortages, thereby lowering the purchasing costs for bus operators.

关键词： Traffic engineering Connected electric bus scheduling mixed integer linear programming Arterial signal coordination coordination Static wireless charging

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Multi-Agent Grouping and Routing with Cooperative Tasks

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JOURNAL OF AEROSPACE INFORMATION SYSTEMS 2025年第3期22卷 163-176页

作者： Choi, Euihyeon Ahn, Jaemyung Korea Adv Inst Sci & Technol KAIST Dept Aerosp Engn 291 Daehak Ro Daejeon 34141 South Korea

This paper introduces a grouping and routing problem of multiple agents for cooperative missions. The introduced problem, referred to as the Vehicle Grouping and Routing Problem with Profits, aims to maximize the total reward obtained by conducting a multi-agent mission (e.g., cooperative reconnaissance) while reducing its makespan by appropriately grouping the agents and determining their routes under operational constraints (e.g., fuel, endurance). A mixed-integer linear programming formulation and a conservative column generation-based solution procedure for the problem are proposed. A case study with homogeneous and heterogeneous agents and numerical experiments involving a cooperative reconnaissance mission with multiple unmanned aerial vehicles demonstrate the validity of the proposed formulation and solution procedure.

关键词： Unmanned Aerial Vehicle mixed integer linear programming Optimization Algorithm Flight Dynamics Autonomous Technology Planetary Science and Exploration Aerospace Engineering

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Analysis of the inter-city shared mobility system based on autonomous electric vehicles

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RENEWABLE ENERGY 2025年 239卷

作者： Wang, Peng Jiang, Han Cui, Yanlei Zhao, Mingming Ren, Yilong Xu, Liang Beihang Univ Hangzhou Innovat Inst Beijing Peoples R China Beihang Univ Sch Transportat Sci & Engn Beijing Peoples R China Beihang Univ State Key Lab Intelligent Transportat Syst Beijing Peoples R China Xidian Univ State Key Lab Integrated Serv Networks Xian Peoples R China Xidian Univ Hangzhou Inst Technol Hangzhou Peoples R China

While autonomous electric vehicles (AEVs) have been preliminarily implemented in shared travel services from both technical and theoretical perspectives, challenges such as dispersed fleets, limited service quality, and travel safety concerns have confined existing research to intra-city shared mobility, with few studies focusing on inter-city shared mobility for AEVs. With China's metropolitan regions expanding and intercity travel rapidly increasing, examining the use of shared autonomous electric vehicles (SAEVs) for intercity travel is essential for future transportation systems. To address this issue, this study models the inter-city shared mobility problem utilizing mixed integer linear programming. The problem is defined on a directed graph and addressed using a variable neighborhood search algorithm. Numerical experiments are designed based on the actual shared mobility data between Yinchuan and Shizuishan, Ningxia Province, China. From the perspective of the operating platform, the potential influencing factors of the inter-city shared mobility system are analyzed, including passenger travel demand, fleet size, vehicle range, and the number of charging stations. The results demonstrate that increasing temporal and spatial imbalance in passenger travel demand and excessive fleet size will lead to lower total revenue of the operation platform. Conversely, within certain thresholds, increasing the number of charging stations, vehicle range, and fleet size will increase the total revenue. Continuing to increase the number of charging stations and vehicle range has no significant effect on total revenue and service rate but will lead to a waste of basic resources. The study is expected to provide solution for building an inter-city shared mobility system based on SAEVs. By fully understanding the system's limitations and advantages, we aim to provide a reference template for constructing future inter-city shared mobility systems.

关键词： Shared autonomous electric vehicle Inter-city shared mobility system mixed integer linear programming Variable neighborhood search

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Comparison of CD and CDC Technologies for Flex Grid DWDM Networks

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IEEE ACCESS 2024年 12卷 116026-116039页

作者： Kozdrowski, Stanislaw Krysztofik, Pawel Sujecki, Slawomir Warsaw Univ Technol Comp Sci Inst PL-00665 Warsaw Poland Wroclaw Univ Sci & Technol Telecommun & Teleinformat Dept PL-50370 Wroclaw Poland Mil Univ Technol Fac Elect PL-00908 Warsaw Poland

The main objective of the paper is to compare CD and CDC nodal architecture technologies for flex grid DWDM optical networks. The methodology adopted consists in optimising a DWDM network for both nodal architectures and comparing the resource utilisation. Several nature-inspired heuristic algorithms, based mainly on an evolutionary algorithm, have been specifically selected to solve the optimisation problem with realistic computational resources. Numerical experiments were carried out for two distinct backbone networks: Polish and American. Using the best of the proposed heuristic methods in terms of the value of the objective function and computation time, CD and CDC technologies were compared. The results obtained show the advantages of CDC technology over CD technology, particularly with respect to utilization of occupied frequency bandwidth of network edges.

关键词： Wavelength division multiplexing Optimization Bandwidth Costs Transponders Routing Mathematical models Metaheuristics Evolutionary computation mixed integer linear programming Optical fiber networks evolutionary algorithm bees algorithm mixed integer linear programming combinatorial optimization new-generation optical network design DWDM CD CDC

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Optimizing battery storage for sustainable energy communities: A multi-scenario analysis

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SUSTAINABLE CITIES AND SOCIETY 2025年 118卷

作者： Guo, Feng Gomes, Luis Ma, Ling Tian, Zhiyong Vale, Zita Pang, Shiyuan Huazhong Univ Sci & Technol Natl Ctr Technol Innovat Digital Construct Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Sch Civil & Hydraul Engn Wuhan 430074 Peoples R China Polytech Porto LASI Intelligent Syst Associate Lab GECAD Res Grp Intelligent Engn & Comp Adv Innovat Porto Portugal Huazhong Univ Sci & Technol Sch Environm Sci & Engn Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Sch Environm Sci & Engn Hubei Key Lab Multimedia Pollut Cooperat Control Y Wuhan 430074 Peoples R China Huadian Jinsha River Upstream Hydropower Dev Co Lt Chengdu 610041 Peoples R China

The Energy Community (EC) is expanding worldwide, with Solar Photovoltaic (PV) systems as the primary Renewable Energy Source (RES). However, "solar curtailment" challenges the European Union's 2030 Target of achieving 45 % renewables in final energy consumption. Peer-to-peer (P2P) energy sharing and Battery Energy Storage Systems (BESS) sharing can improve the RES share more effectively, but they face obstacles like high costs and low utilisation rates. This research develops a hybrid model that combines P2P energy sharing with BESS, optimised using mixed integer linear programming (MILP). A new pricing mechanism for P2P transactions and refined Shapley value calculations are introduced. Simulations conducted over 672 h across four seasons and 21,147 scenarios demonstrate that all proposed models effectively increase the renewable energy share. SBES-S and OCBES-S models are the most economical in spring and summer, with EC costs of -13.028 and -55.578. The OCBES-S model is the most cost-effective for autumn and the year, costing 92.998 and 174.101, respectively. Compared to the scenario without BESS and P2P sharing, it reduces annual electricity costs by 16.34 %. This study provides all EC stakeholders with a tool for option comparison and economic analysis, supporting the sustainable development of EC and renewable energy.

关键词： Energy community Battery energy storage systems Peer to peer mixed integer linear programming Renewable energy Sustainable development

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A Resilience Enhancement Planning Framework Capturing Customers' Participation in Distribution Systems

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IEEE TRANSACTIONS ON SMART GRID 2025年第2期16卷 957-972页

作者： Eshkaftaki, Amin Alavi Latify, Mohammad Amin Fotuhi-Firuzabad, Mahmoud Dehghanian, Payman Isfahan Univ Technol Dept Elect & Comp Engn Esfahan *** Iran Sharif Univ Technol Dept Elect Engn Tehran 111554363 Iran George Washington Univ Dept Elect & Comp Engn Washington DC 20052 USA

This paper presents a novel planning framework to enhance the resilience of energy supply to customers in power distribution systems. The framework involves three key stakeholders: the regulator as the governing entity that enforces regulatory mechanisms to oversee the performance of the distribution system operator (DSO);the DSO that reinforces the infrastructure by placing emergency distributed generations and hardening sections, implements necessary operational decisions, and facilitates customers' participation by introducing appropriate incentives;and customers who may (i) gain the desired resilience through investing in self-generation, (ii) rely on the resilience provided by the DSO along with paying the agreed-upon insurance premiums, or (iii) opt for a mix of both approaches. The proposed framework is designed through a four-step process. First, the regulatory mechanisms are established by setting a standard resilience index for the penalty and reward model as well as a revenue cap for the DSO under a revenue-cap regulation using customized optimization problems aimed at optimizing DSO's costs without customers' participation. Next, an integrated resilience enhancement optimization problem that coordinates the strategies of the DSO and customers is formulated as a mixed-integer linear programming model, focusing on the global objective functions of the DSO and customers. Finally, the economic benefits are distributed between the DSO and customers who are justified for investment in self-generation using a suggested method based on Monte-Carlo estimation, in which the Fisher-Yates shuffle technique and a designated optimization problem are employed. Applied to the IEEE 33-bus test system for two case studies, the proposed framework is proven to be effective in enhancing resilience, achieving regulatory objectives, and providing economic benefits for both the DSO and customers, creating a mutually beneficial scenario for all parties involved.

关键词： Resilience Reactive power Planning Costs Investment Indexes linear programming Fault tolerance Substations mixed integer linear programming Customers disruptive events distribution system operator (DSO) mixed-integer linear programming (MILP) regulator resilience

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Integrated Planning Model for Optimizing Investments in Hydrogen Infrastructure Deployment: A Case Study of Yangtze River Delta Region, China

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ENERGY SCIENCE & ENGINEERING 2025年第3期13卷 1306-1322页

作者： Shen, Weijie Li, Hua Ding, Hongjian Zeng, Ming Xie, Chuansheng Zhang, Xiaochun North China Elect Power Univ Sch Econ & Management Beijing Peoples R China PowerChina Huadong Engn Corp Ltd Hangzhou Peoples R China

The hydrogen industry is of great significance for global energy system transition and decarbonization;thus, the holistic planning of hydrogen infrastructure from a supply chain level is necessary. To this end, first, the framework and methods in the hydrogen infrastructure deployment research were investigated systematically. Second, a hydrogen supply chain design (HSCD) model and a hydrogen refueling station location (HRSL) model were constructed. In view of the limitations of the two models, this paper reformulated the HRSL model through alternating the objective function and constraint, then proposed an integrated planning model using the & varepsilon;${\epsilon}$-constraint method, which relaxed the assumption condition and expanded the decision-making boundary of the original model, realizing the reasonable equilibrium of multiple segments. Finally, a case study was conducted using the Yangtze River Delta region as an example, and the main findings were as follows: (1) To meet the hydrogen demand of 25494t/d, the Yangtze River Delta region needs to build 94 coal gasification hydrogen plants, storage facilities with capacity of 12747t, transmission modes with capacity of 2333t/d, and 150 hydrogen refueling stations. (2) Railways have more advantages in large capacity and long-distance hydrogen transmission. (3) Road segments with higher traffic flow often have a higher capture proportion. (4) The investment cost accounts for the majority of hydrogen production plant construction, which is 43.80%.

关键词： hydrogen refueling station location hydrogen supply chain design mixed integer linear programming Yangtze River Delta region

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Disaster risk-informed optimization using buffered failure probability for regional-scale building retrofit strategy

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STRUCTURAL SAFETY 2025年 114卷

作者： Seok, Uichan Byun, Ji-Eun Song, Junho Seoul Natl Univ Dept Civil & Environm Engn Seoul South Korea Univ Glasgow James Watt Sch Engn Glasgow Scotland

Regional retrofit planning of buildings is critical to address the increasing threat of natural disasters exacerbated by urban growth and climate change. To identify an optimal plan, this paper introduces a novel optimization framework. By integrating performance-based engineering (PBE) and reliability-based optimization (RBO), we propose buffered optimization and reliability method based mixed integer linear programming (BORM-MILP). The proposed formulation can identify optimal solutions using general optimization solvers, while handling a large number of PBE samples and buildings. Furthermore, the formulation introduces a modified active-set strategy tailored to regional-scale building retrofit optimization problems, further reducing computational memory. The proposed optimization framework is validated by a benchmark example of Seaside, Oregon. The optimization results are presented along in a map, offering visual support for decision-making processes. The application results are further investigated to analyze computational efficiency of the proposed active-set strategy, study convergence to the normal distribution, and identify a dominant factor for the building retrofit selection.

关键词： Building retrofit Performance-based engineering Reliability-based optimization Buffered failure probability mixed integer linear programming Community resilience

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