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Explicit Resilience Assessment Model for Distribution Systems With Arbitrary Protection and Switching Equipment Configuration

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IEEE TRANSACTIONS ON POWER DELIVERY 2025年第2期40卷 1089-1099页

作者： Sun, Yaqi Wu, Wenchuan Tsinghua Univ Dept Elect Engn State Key Lab Power Syst Beijing 100084 Peoples R China

The power outages caused by extreme events are becoming more frequently and damage the distribution networks in recent years. Therefore, the concept of resilience was proposed to measure the performance of the distribution systems in high-impact and low-probability (HILP) events. In this paper, we propose an explicit resilience assessment model for the distribution networks. For HILP events, an explicit formulation model is proposed to describe the evolution of the distribution system from the contingencies occurrence to system recovery, in which the actions of protection and switch equipment, such as circuit breakers, automatic switches and manual switches, are fully considered. Based on this formulation, an explicit resilience assessment model considering the maintenance resource constraints is developed, which embeds the optimization of outage recovery sequence. The resilience assessment model is finally cast as an instance of mixed integer linear programming (MILP). Case study on the modified IEEE 33-node and IEEE 123-node systems is performed and the effectiveness of proposed method is verified.

关键词： Resilience Circuit faults Contingency management Load modeling Switches Distribution networks Circuit breakers Numerical models Power supplies Maintenance engineering Distribution network resilience assessment high-impact and low-probability event mixed integer linear programming

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Road network, landing location, and routing optimization for forest smallholders landscapes

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INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 2025年第2期32卷 888-917页

作者： Constantino, Miguel F. Mesquita, Marta Marques, Susete Toth, Sandor F. Borges, Jose G. Univ Lisbon Fac Ciencias Ctr Matemat & Aplicacoes Fundamentais & Invest Ope P1749016 Lisbon Portugal Univ Lisbon Fac Ciencias DEIO P-1749016 Lisbon Portugal Univ Lisbon ISA P-1349017 Lisbon Portugal Ctr Estudos Florestais & Associate Lab TERRA P-1349017 Lisbon Portugal Univ Washington Sch Environm & Forest Sci Seattle WA 98195 USA

We present two mixed integer linear programming (MILP) formulations for a well-known integrated network, timber landing location, and routing problem that arises in forest management. The models seek to jointly optimize the construction and maintenance schedule of forest road networks with landing site selection and transportation routing for timber production. This problem is, in general, difficult to solve as it contains the so-called fixed charge network flow problem, which is known to be NP-hard. One of the proposed MILP formulations considers 3-index continuous variables to represent timber flows on road segments in each period. The presence of Big-M constraints leads to weak linear relaxation bounds. Disaggregating flow variables, according to timber origin, results in a novel 4-index formulation with very tight linear relaxation bounds. Nevertheless, the number of variables increases prohibitively. This research makes use of spatial constraints common to Smallholding Forested Landscapes to develop a solution approach that reduces the number of flow variables in the new 4-index model. Results from a real-world case study located in Northwest Portugal show that, with the 4-index formulation, the proposed solution approach makes it possible to obtain optimal solutions in a short computational time.

关键词： OR in natural resources forest road network optimization mixed integer linear programming

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A Probabilistic Hesitant Fuzzy Multi-Criteria Decision-Making Method Based on CSOGRMILP and Borda-CoCoSo

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INTERNATIONAL JOURNAL OF FUZZY SYSTEMS 2025年 1-18页

作者： Su, Jiafu Xu, Baojian Liu, Hongyu Chen, Yijun Zhang, Xiaoli Chongqing Technol & Business Univ Natl Res Base Intelligent Mfg Serv Chongqing Peoples R China Krirk Univ Int Coll Bangkok Thailand Anhui Tech Coll Mech & Elect Engn Sch Econ & Trade Wuhu Peoples R China

This paper proposes a multi-criteria decision-making method based on CSOGRMILP and Borda-CoCoSo in a probabilistic hesitant fuzzy environment. In this method, we utilize a probabilistic hesitant fuzzy scoring function to process the probabilistic hesitant fuzzy information, obtaining a processed decision matrix. Then, based on the processed decision matrix, we propose the "Combined Subjective-Objective, Gray Relational Analysis, mixed integer linear programming" (CSOGRMILP) method to determine the weights of decision criteria. Next, an improved method called Borda-CoCoSo is proposed for ranking solutions based on the Borda rule modification of the Combined Comprise Solution (CoCoSo) method. Finally, a case study on the selection of degradable dynamic plastic products was used to validate the proposed method. In the comparative analysis, we compare the proposed method with traditional methods. This further validates the rationality of the Borda-CoCoSo method. Additionally, we compare CSOGRMILP with EWM (Entropy Weight Method), MEREC (MEthod based on the Removal Effects of Criteria), CRITIC (CRiteria Importance Through Inter-criteria Correlation), and ROSOSD (The Robustness, Correlation, and Standard Deviation). The comparison results indicate that CSOGRMILP demonstrates better stability (0.046) and the best consistency (96.43%).

关键词： Weighting method Borda rule Gray relational analysis mixed integer linear programming Multi-criteria decision-making

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Cooperative dispatch of demand response and stability constrained transfer capability for inter-connected power systems: A hybrid learning-aided method

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APPLIED ENERGY 2025年 381卷

作者： Liu, Ji'ang Liu, Youbo Qiu, Gao Chen, Gang Xu, Lixiong Liu, Junyong Sichuan Univ Coll Elect Engn Chengdu 610065 Sichuan Peoples R China State Grid Sichuan Elect Power Res Inst Chengdu 610065 Sichuan Peoples R China

Reverse peak conditions in generation and load profiles, as well as limiting total transfer capability (TTC) of power transmission inter-corridors, are critical inducements of renewable curtailment. Despite demand response (DR) incents loads to better complement renewable generations, it can in turn aggravate hindrance of renewable energies' exporting consumption. To solve this issue, spatiotemporal cooperation between DR and TTC must be involved. Further challenge relates to complicated interaction between price-incentive DR and stability constrained TTC. A hybrid learning-aided cooperative dispatch method is thus proposed. Firstly, to mitigate overconservative power transfer and reduce the high-dimensional dynamic security bounds, a neural network is introduced to fast track dynamic TTC varying with the dispatch model. It is then reformulated as mixed integer linear programming (MILP) and seamlessly integrated into the optimization process along with price-based DRs. At last, to help fast approach optimum of the DR-TTC-cooperative model, a physics-regularized temporal graph convolutional network is utilized to warmly initialize units' on/off status, DRs and energy storages' active states, and auxiliary integer variables introduced from MILP-reformed TTC estimator as well. Case studies on the modified IEEE 39-bus system verify that our method outperforms traditional method regarding security adherence and efficiency, and reveal the importance of DR and TTC's cooperation in releasing renewable consumption latency.

关键词： Stability constrained total transfer capability Cooperative dispatch model Hybrid learning-aided method Demand response mixed integer linear programming

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A metaheuristic algorithm for efficient aircraft sequencing and scheduling in terminal maneuvering areas

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OPTIMIZATION LETTERS 2025年第3期19卷 579-604页

作者： Gui, Dongdong Le, Meilong Luo, Xiaodong Huang, Zhouchun Nanjing Univ Aeronaut & Astronaut Coll Civil Aviat Nanjing Peoples R China Nanjing Univ Aeronaut & Astronaut Coll Econ & Management Nanjing Peoples R China Shenzhen Res Inst Big Data Shenzhen Peoples R China

Air traffic controllers face a daily challenge ensuring the safe and orderly flow of aircraft in terminal maneuvering areas, known academically as the Aircraft Sequencing and Scheduling Problem (ASSP). Typically formulated as a mixed integer linear programming problem, the strong NP-hard nature of the ASSP necessitates the use of heuristics or metaheuristics for practical, time-efficient solutions. In this paper, we propose a new metaheuristic algorithm to address the computational complexity of the problem. The algorithm employs a single-solution-based search methodology that starts from a well-constructed initial solution and iteratively explores a fix-and-optimize procedure to find an improved solution. Specifically, this procedure solves a variant of the ASSP that contains all the continuous variables and a selected subset of binary variables of the original problem, with the remaining binary variables being temporarily fixed to the values determined based on previous iterations. Additionally, the algorithm incorporates tabu search to increase the possibility of quickly finding optimal solutions. A rolling horizon control approach further accelerates the solution derivation process by decomposing the original problem into smaller subproblems. Our computational experiments using real traffic data from Guangzhou Baiyun International Airport demonstrates the effectiveness of the algorithm in terms of solution quality and computational time.

关键词： Aircraft sequencing and scheduling Metaheuristic algorithm mixed integer linear programming Fix-and-optimize

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Model-based algorithms for the 0-1 Time-Bomb Knapsack Problem

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COMPUTERS & OPERATIONS RESEARCH 2025年 178卷

作者： Montemanni, Roberto Smith, Derek H. Univ Modena & Reggio Emilia Dept Sci & Methods Engn Via Amendola 2 I-42122 Reggio Emilia Italy Univ South Wales Comp & Math Pontypridd CF37 1DL Wales

A stochastic version of the 0-1 Knapsack Problem recently introduced in the literature and named the 0-1 Time-Bomb Knapsack Problem is the topic of the present work. In this problem, in addition to profit and weight, each item is characterized by a probability of exploding, and therefore destroying all the contents of the knapsack, incase it is loaded. The optimization aims at maximizing the expected profit of the selected items, which takes into account also the probabilities of explosion, while fulfilling the capacity constraint. The problem has real-world applications in logistics and cloud computing. In this work, two model-based algorithms are introduced. They are based on partial linearizations of a non-linear model describing the problem. Extensive computational results on the instances available in the literature are presented to position the new methods as the best-performing ones, while comparing against those previously proposed.

关键词： 0-1 Knapsack Time-bomb Model-based algorithms mixed integer linear programming

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A Novel Mathematical Model for the Flexible Job-Shop Scheduling Problem With Limited Automated Guided Vehicles

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2025年 22卷 7449-7462页

作者： Yao, Youjie Liu, Qihao Fu, Ling Li, Xinyu Yu, Yanbin Gao, Liang Zhou, Wei Huazhong Univ Sci & Technol State Key Lab Intelligent Mfg Equipment & Technol Wuhan 430074 Peoples R China Siemens Technol Shanghai 430074 Peoples R China Siemens Technol Wuhan 430074 Peoples R China

Automated Guided Vehicles (AGVs) have found widespread application in discrete manufacturing systems. In flexible job-shop environments, the integrated scheduling of machines and AGVs is a significant research direction to improve the productivity. However, the existing mathematical model assigns non-existent transport tasks to the corresponding AGVs, resulting in poor performance. To tackle this weakness, this paper proposes a novel mixed integer linear programming (MILP) model. Firstly, the flexible job-shop scheduling problem with limited AGVs (FJSPLA) is decomposed into four sub-problems, and the interactions and dependencies between the sub-problems are elaborated. Secondly, the existence of transport tasks is explained in detail based on the disjunctive graph model. Subsequently, a more efficient MILP model is proposed, leveraging insights from the four sub-problems and the disjunctive graph model. Finally, comparison experiments are conducted, encompassing two benchmarks (FJSPT and EX), along with a real-world case. The proposed model exhibits a more streamlined formulation with fewer decision variables and constraints in comparison to existing models. It successfully proves optimality for the most challenging instance FJSPT7 as well as 15 instances in EX benchmark. Compared with the existing model, the experimental results not only demonstrate the effectiveness and superior performance of the proposed model but also show the practicality in addressing real workshop problems.

关键词： Task analysis Mathematical models Job shop scheduling Benchmark testing Production Genetic algorithms Conferences Integrated scheduling flexible job shop scheduling problem AGV scheduling mixed integer linear programming

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MILP optimization of the multi-heat pump waste heat recovery system integrated with full-free cooling data center through lake water

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ENERGY 2025年 318卷

作者： Chen, Shuyi Zhang, Quan Zhai, John Liu, Haowen Chen, Gang Lei, Jianjun Liao, Shuguang Hunan Univ Coll Civil Engn Changsha 410082 Peoples R China Univ Colorado Boulder Dept Civil Environm & Architectural Engn Boulder CO 80309 USA Hong Kong Polytech Univ Dept Bldg Serv Engn Hong Kong Peoples R China Univ South China Coll Civil Engn Hengyang 421001 Peoples R China Hunan Cloud Nest Informat Technol Co Ltd Chenzhou 423400 Peoples R China Changsha Mairong High Tech Co Ltd Changsha 410015 Peoples R China

Free cooling and waste heat recovery are vital and promising energy-saving technologies for the cooling system of data centers and the heating system of nearby buildings. The multi-heat pump system with different heat capacities is one of the most effective ways to extract heat from data centers, which need to match the cooling and heating demand in varied times and spaces. It will improve the performance of the integrated system, however, it raises their complexity and decreases the reliability. This study developed a comprehensive model from the computer room to heat consumers, mainly including information technology (IT) equipment heat dissipation, computer room air handler (CRAH), heat exchanger, water pump, heat pump, and thermal energy storage tank (TES). Based on mixed integer linear programming (MILP), an optimization control strategy was used to save energy without sacrificing the data center's reliability by regulating key operating parameters, such as the partial load ratio (PLR) of the heat pump, the ON-OFF mode, water pump's flow rate, and the heat storage and release mode of TES. Compared to the rule-based strategy, the MILP-based strategy improved the heat pump's daily average coefficient of performance (COP) and the heating system's energysaving rate by 1.19 and 15.11 % in winter, 1.21 and 14.68 % in the transition season, 1.13 and 12.91 % in summer, respectively. The related energy consumption of the cooling system in the above three seasons decreased by 3.78 %, 3.50 %, and 3.38 %, and the annual power usage effectiveness (PUE) reduced by 0.01. The annual energy-saving rate of the whole system was 8.12 %, and its global coefficient of performance (GCOP) increased from 9.96 to 10.85.

关键词： Data center Heat pump Waste heat recovery mixed integer linear programming Operation optimization

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Quantifying performance indicators in perishable food supply chain networks: Assessing dynamic performance under ripple effects

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COMPUTERS & INDUSTRIAL ENGINEERING 2025年 201卷

作者： Karanam, Malleswari Krishnanand, Lanka Manupati, Vijaya Kumar NIT Warangal Dept Mech Engn Warangal Telangana India Indian Inst Management Mumbai Operat & Supply Chain Div Mumbai India

Developing an efficient and resilient perishable food supply chain network (PFSCN) is crucial for cost-effective and timely delivery from suppliers to deficit and surplus regions under disturbed situations. In this paper, we formulated a multi-objective mixed-integer linear programming (MILP) model for a perishable food supply chain (PFSC) under static and dynamic conditions, with the objective of minimizing total cost (TC) and total time (TT) while considering several realistic constraints. As the problem is computationally complex and non-polynomial deterministic (NP-hard), an evolutionary algorithm-based approach is considered. To tackle the problem, first, we considered a static condition and proposed a modified non-dominated sorting genetic algorithm (MNSGA-II) and then compared it to a non-dominated sorting genetic algorithm (NSGA-II). Later, for dynamic conditions, a heuristic method based on the degree of disruption (DOD) and node threshold (NT) has been proposed for estimating the impact of the ripple effect and its impact on PFSCN. Furthermore, the performance characteristics such as TC, TT, Service Level (SL), robustness, resilience, adaptability, efficiency, and centralization were quantified by varying the DOD and NT across various scenarios. To validate the method, extensive computer experiments are conducted, including a case study and sensitivity analysis. Finally, the results reveal that the proposed method outperforms almost all instances.

关键词： Perishable food supply chain network Meta-heuristic algorithms Ripple effect mixed integer linear programming Disruption

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Simultaneous planning of standpoints and routing for laser scanning of buildings with network redundancy

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ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 2025年 224卷 59-74页

作者： Knechtel, Julius Dehbi, Youness Klingbeil, Lasse Haunert, Jan-Henrik Univ Bonn Inst Geodesy & Geoinformat Meckenheimer Allee 172 D-53115 Bonn Germany HafenCity Univ Computat Methods Lab Henning Voscherau Pl 1 D-20457 Hamburg Germany

Stop-and-go laser scanning is becoming increasingly prevalent in a variety of applications, e.g., the survey of the built environment. For this, a surveyor needs to select a set of standpoints as well as the route between them. This choice, however, has a high impact on both the economic efficiency of the respective survey as well as the completeness, accuracy, and subsequent registrability of the resulting point cloud. Assuming a set of building footprints as input, this article proposes a one-step optimization method to find the minimal number of selected standpoints based on scanner-related constraints. At the same time, we incorporate the length of the shortest route connecting the standpoints in the objective function. A local search method to speed up the time for solving the corresponding mixed-integer linear Program (MILP) is additionally presented. The results for different scenarios show constantly shorter routes in comparison to existing approaches while still maintaining the minimal number of standpoints. Moreover, in our formulation we aim to minimize the effects of inaccuracies in the software-based registration. Inspired by the ideas of network survivability, we to this end propose a novel definition of connectivity tailored for laser scanning networks. On this basis, we enforce redundancy for the registration network of the survey. To prove the applicability of our formulation, we applied it to a large real-world scenario. This paves the way for the future use of fully automatic autonomous systems to provide a complete and high-quality model of the underlying building scenery.

关键词： Laser scanning Network survivability Optimization Redundancy mixed integer linear programming Route planning

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