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在城市风险增加和政府政策推动的双重背景下,韧性城市的建设进程加快,随之而来的运营管理问题已逐渐成为一个新兴的研究热点.韧性城市运营管理旨在运用复杂运营管理的思想、方法和技术,提升城市风险应对能力,优化城市资源配置,为增强城市安全韧性和推动城市治理体系现代化提供决策支持.本文基于2013-2023年国内外韧性城市运营管理相关文献,结合韧性城市运营管理内涵,运用定量分析与定性分析相结合的方式,归纳出韧性城市运营管理的交通管理、物流管理、水资源与能源管理、环境管理、安全管理和智慧发展六大主要研究领域,总结了各领域的研究进展,提炼出韧性城市运营管理研究的关注热点,并结合最新的研究成果分析了相关领域研究的必要性和紧迫性.
Keyword ：
资源优化 资源优化 运营管理 运营管理 韧性城市 韧性城市 风险应对 风险应对
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| GB/T 7714 | 吴鹏 , 王琦 , 霍红 et al. 韧性城市运营管理:新兴研究热点及其进展 [J]. | 中国管理科学 , 2025 , 33 (1) : 34-51 . |
| MLA | 吴鹏 et al. "韧性城市运营管理:新兴研究热点及其进展" . | 中国管理科学 33 . 1 (2025) : 34-51 . |
| APA | 吴鹏 , 王琦 , 霍红 , 刘作仪 . 韧性城市运营管理:新兴研究热点及其进展 . | 中国管理科学 , 2025 , 33 (1) , 34-51 . |
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In this study, we address a new dynamic scheduling-location problem (DSLP), which is that incorporates movable machines. The objective is designed to optimize job scheduling and machine placement dynamically. For this strongly NP-hard problem, we formulate the problem as a mixed-integer linear programming (MILP) model. To further improve its computational efficiency and tighten the lower bounds for faster convergence to optimal solutions, we propose several valid inequalities based on the characteristics of the DSLP. Numerical experimental results for a case and randomly generated instances demonstrate significant improvements in system efficiency by allowing machine movement. The findings highlight the potential of extending traditional location scheduling frameworks to include dynamic elements, offering new insights and practical implications for complex industrial applications. © 2024 IEEE.
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| GB/T 7714 | Hu, J. , Wu, P. . Integrated Scheduling and Location Considering Machine Mobility [未知]. |
| MLA | Hu, J. et al. "Integrated Scheduling and Location Considering Machine Mobility" [未知]. |
| APA | Hu, J. , Wu, P. . Integrated Scheduling and Location Considering Machine Mobility [未知]. |
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针对制造业和服务业等领域中广泛存在的多资源工序资源分配问题,考虑工件和可移动类资源的运输时间,以最小化最长完工时间为优化目标,构建一类新的资源分配混合整数线性规划模型.针对该问题特性,提出变邻域搜索模拟退火的混合算法.该算法结合变邻域搜索算法局部搜索能力强和模拟退火算法全局寻优的优势,同时克服前者容易陷入局部最优而后者局部收敛不佳的问题.在算法的设计中,引入自适应邻域结构和改进降温函数以提高算法的收敛效率.300 个不同规模的仿真算例实验结果表明,在求解大规模实例中,所提算法的性能均优于CPLEX求解器、变邻域搜索算法和模拟退火算法,能提供更好的资源分配方案.
Keyword ：
变邻域算法 变邻域算法 多资源工序 多资源工序 模拟退火算法 模拟退火算法 资源分配 资源分配 运输时间 运输时间
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| GB/T 7714 | 翁武燕 , 储诚斌 , 吴鹏 . 考虑运输时间的多资源工序的资源分配优化 [J]. | 福州大学学报（哲学社会科学版） , 2024 , 38 (4) : 72-80 . |
| MLA | 翁武燕 et al. "考虑运输时间的多资源工序的资源分配优化" . | 福州大学学报（哲学社会科学版） 38 . 4 (2024) : 72-80 . |
| APA | 翁武燕 , 储诚斌 , 吴鹏 . 考虑运输时间的多资源工序的资源分配优化 . | 福州大学学报（哲学社会科学版） , 2024 , 38 (4) , 72-80 . |
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针对广泛存在于制造业和服务业等现实应用中的需要多类资源的多资源工序,提炼出一类新的带多资源工序的资源分配问题.建立了以最小化最大完工时间为目标的混合整数线性规划模型,并根据问题特征设计了改进禁忌搜索算法.在算法设计中,通过扰动策略和自适应禁忌长度避免陷入局部最优.300个不同规模仿真算例实验结果表明:在求解大规模实例中,改进禁忌搜索算法的性能表现优于CPLEX、经典禁忌搜索算法、变邻域搜索算法和遗传算法,能给出更好的资源分配方案;与CPLEX相比,目标函数值改善了 3.01％.
Keyword ：
基于资源分配的先后次序 基于资源分配的先后次序 带多资源工序 带多资源工序 禁忌搜索算法 禁忌搜索算法 资源分配 资源分配
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| GB/T 7714 | 翁武燕 , 储诚斌 , 吴鹏 . 一类带多资源工序的资源分配优化方法 [J]. | 计算机工程与应用 , 2024 , 60 (21) : 324-330 . |
| MLA | 翁武燕 et al. "一类带多资源工序的资源分配优化方法" . | 计算机工程与应用 60 . 21 (2024) : 324-330 . |
| APA | 翁武燕 , 储诚斌 , 吴鹏 . 一类带多资源工序的资源分配优化方法 . | 计算机工程与应用 , 2024 , 60 (21) , 324-330 . |
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This paper investigates a new resource-allocation problem involving multi-resource oper-ations,where completing an operation requires simultaneous use of multiple(renewable)resources,probably of different types.The goal of the study is to provide a solution method that minimizes the makespan.The authors formulate the problem into a novel mixed-integer linear program(MILP)model.To efficiently solve practical-sized instances,an exact Benders decomposition algorithm is de-veloped.This algorithm divides the original problem into a master problem of allocating resources and a subproblem of calculating the makespan,and both are linked via Benders cuts.The convergence is sped up by improving the mathematical model and embedding the variable neighborhood search algo-rithm.Compared with CPLEX,a commonly used MILP solver,the computational results demonstrate that the proposed algorithm provides tighter upper and lower bounds in most instances.In particular,compared with CPLEX,the proposed method can on average improve the upper and lower bounds by 4.76％ and 4.39％,respectively,in solving practical-sized instances.
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| GB/T 7714 | WENG Wuyan , CHU Chengbin , WU Peng . Resource Allocation to Minimize the Makespan with Multi-Resource Operations [J]. | 系统科学与复杂性学报（英文版） , 2024 , 37 (5) : 2054-2070 . |
| MLA | WENG Wuyan et al. "Resource Allocation to Minimize the Makespan with Multi-Resource Operations" . | 系统科学与复杂性学报（英文版） 37 . 5 (2024) : 2054-2070 . |
| APA | WENG Wuyan , CHU Chengbin , WU Peng . Resource Allocation to Minimize the Makespan with Multi-Resource Operations . | 系统科学与复杂性学报（英文版） , 2024 , 37 (5) , 2054-2070 . |
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Abstract ：
针对现实中广泛存在的多资源工序的资源分配问题,考虑基于资源使用的优先次序约束,以最小化加权完工时间为优化目标,构建一类新的资源分配混合整数线性规划模型.其次,提出Benders分解和禁忌搜索的混合算法,该混合算法以Benders分解为基本框架,将原问题分为提供资源分配方案的主问题和计算工序加权完工时间的子问题,并通过改进数学模型和添加禁忌搜索提高混合算法的收敛速度.最后,通过300个随机仿真算例测试结果表明,在相同时间下求解小规模问题时,所提的Benders分解混合算法能获得距离商业求解器CPLEX最优解平均差距为0.86%的满意解;在求解大规模问题时,所提出的算法的性能表现优于CPLEX、禁忌搜索算法、变邻域搜索算法和Benders分解嵌入遗传算法的混合方法,能给出更好的资源分配方案,与CPLEX相比,上界和下界分别改善了4.74%和9.62%.
Keyword ：
Benders分解 Benders分解 基于资源使用的先后次序 基于资源使用的先后次序 多资源工序 多资源工序 禁忌搜索算法 禁忌搜索算法 资源分配 资源分配
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| GB/T 7714 | 翁武燕 , 储诚斌 , 吴鹏 . 极小化加权完工时间的多资源工序的资源分配问题 [J]. | 控制与决策 , 2024 , 39 (08) : 2765-2772 . |
| MLA | 翁武燕 et al. "极小化加权完工时间的多资源工序的资源分配问题" . | 控制与决策 39 . 08 (2024) : 2765-2772 . |
| APA | 翁武燕 , 储诚斌 , 吴鹏 . 极小化加权完工时间的多资源工序的资源分配问题 . | 控制与决策 , 2024 , 39 (08) , 2765-2772 . |
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Abstract ：
This paper investigates a new resource-allocation problem involving multi-resource operations, where completing an operation requires simultaneous use of multiple (renewable) resources, probably of different types. The goal of the study is to provide a solution method that minimizes the makespan. The authors formulate the problem into a novel mixed-integer linear program (MILP) model. To efficiently solve practical-sized instances, an exact Benders decomposition algorithm is developed. This algorithm divides the original problem into a master problem of allocating resources and a subproblem of calculating the makespan, and both are linked via Benders cuts. The convergence is sped up by improving the mathematical model and embedding the variable neighborhood search algorithm. Compared with CPLEX, a commonly used MILP solver, the computational results demonstrate that the proposed algorithm provides tighter upper and lower bounds in most instances. In particular, compared with CPLEX, the proposed method can on average improve the upper and lower bounds by 4.76% and 4.39%, respectively, in solving practical-sized instances. © The Editorial Office of JSSC & Springer-Verlag GmbH Germany 2024.
Keyword ：
Benders decomposition Benders decomposition multi-resources operations multi-resources operations resource allocation resource allocation
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| GB/T 7714 | Weng, W. , Chu, C. , Wu, P. . Resource Allocation to Minimize the Makespan with Multi-Resource Operations [J]. | Journal of Systems Science and Complexity , 2024 , 37 (5) : 2054-2070 . |
| MLA | Weng, W. et al. "Resource Allocation to Minimize the Makespan with Multi-Resource Operations" . | Journal of Systems Science and Complexity 37 . 5 (2024) : 2054-2070 . |
| APA | Weng, W. , Chu, C. , Wu, P. . Resource Allocation to Minimize the Makespan with Multi-Resource Operations . | Journal of Systems Science and Complexity , 2024 , 37 (5) , 2054-2070 . |
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This work addresses a new bi-objective parallel machine selection and job scheduling problem with release dates and resource consumption. It consists in optimally selecting subcontractors (machines) from a set of geographically dispersed locations and scheduling the orders (jobs) to the selected subcontractors for processing while meeting the order release dates and resource consumption restrictions, so as to simultaneously minimize the maximum completion time, i.e., the makespan, and the total cost including machine usage cost and resource consumption cost. The problem is first formulated into a bi-objective mixed -integer linear program based on linear ordering (LO-MILP), and then valid inequalities are explored based on property analysis. To solve it, an e -constraint method based on LO-MILP (e-LO-MILP) is first proposed. To more efficiently solve it, we also develop a tailored logic -based Benders decomposition combined with e -constraint method (e-LBBD) where a novel method to obtain a tight lower bound of the identical parallel machine with machine -dependent release dates and some problem -specific cuts are proposed. Numerical experiments on an illustrative example are conducted to show the applicability of the model and algorithm and intuitively reveal the trade-off between production efficiency and cost. Experimental results on 200 instances with up to 100 orders demonstrate that e-LBBD can reduce the computation time by about 28.92% compared to e-LO-MILP and yields better Pareto solutions than e-LO-MILP and the well-known non -dominated sorted genetic algorithm II do.
Keyword ：
Logic-based Benders decomposition Logic-based Benders decomposition Parallel machine Parallel machine Release dates Release dates Resource consumption Resource consumption
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| GB/T 7714 | Wu, Peng , Wang, Yun , Chu, Chengbin . Logic-based Benders decomposition for bi-objective parallel machine selection and job scheduling with release dates and resource consumption [J]. | COMPUTERS & OPERATIONS RESEARCH , 2024 , 164 . |
| MLA | Wu, Peng et al. "Logic-based Benders decomposition for bi-objective parallel machine selection and job scheduling with release dates and resource consumption" . | COMPUTERS & OPERATIONS RESEARCH 164 (2024) . |
| APA | Wu, Peng , Wang, Yun , Chu, Chengbin . Logic-based Benders decomposition for bi-objective parallel machine selection and job scheduling with release dates and resource consumption . | COMPUTERS & OPERATIONS RESEARCH , 2024 , 164 . |
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This paper addresses a real life scheduling problem characterised by multi-resource operations whose completion simultaneously requires more than one (renewable) resource of different types. Such problems arise in various companies not only in manufacturing but also in services. Solving such a problem needs to address two interconnected subproblems: a sequencing subproblem and a resource-allocation subproblem if more than one resource is available in some types. The resource-allocation subproblem consists of allocating to each operation the resources it requires while the sequencing subproblem consists of determining the order in which each resource performs the operations assigned to it. This paper focuses on the resource-allocation subproblem. It generalises the basic scheduling problems which consist of determining the operations' starting or completion times for a given processing sequence for every resource. We consider a cost function taking into account the makespan, the cost of resource utilisation, and the load imbalance among the resources of the same type. We first formulate the problem into a mixed-integer linear program (MILP). To efficiently solve it, even in practical-sized instances, an exact algorithm called BD (Benders decomposition with enhancing cuts) is developed where the master problem only considers integer variables. We prove that the slave problem can be transformed into finding the longest paths in a digraph and therefore can be solved with the Bellman-Ford algorithm. To enhance the efficiency of the method, equivalent solutions are limited in the master problem. The performance of the approach is evaluated by comparing it against CPLEX, a state-of-the-art commonplace MILP solver, used to directly solve the initial MILP. The computational results demonstrate that BD provides competitive solutions in all upper and lower bounds. In particular, it improves, compared with CPLEX, the upper and lower bounds by 5.07% and 4.63%, respectively, in solving practical-sized instances. The experiment also shows that considering load balancing can make more rational use of resources and avoid adverse effects caused by excessive workload of staff and imbalanced use of equipment, which is very important in real-world production.
Keyword ：
Benders decomposition Benders decomposition load balancing load balancing multi-resource operations multi-resource operations Resource allocation Resource allocation
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| GB/T 7714 | Weng, Wuyan , Chu, Chengbin , Wu, Peng . A Benders decomposition algorithm for resource allocation with multi-resource operations [J]. | INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH , 2024 , 62 (21) : 7981-7997 . |
| MLA | Weng, Wuyan et al. "A Benders decomposition algorithm for resource allocation with multi-resource operations" . | INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 62 . 21 (2024) : 7981-7997 . |
| APA | Weng, Wuyan , Chu, Chengbin , Wu, Peng . A Benders decomposition algorithm for resource allocation with multi-resource operations . | INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH , 2024 , 62 (21) , 7981-7997 . |
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Limited resources are a prevalent and challenging problem in the field of emergency management. Emergency scheduling is an effective way to make full use of resources. However, designing an effective emergency plan to minimize rescue time is a major challenge. This study focuses on large-scale emergency scheduling for fighting forest fires with multiple rescue centers (depots) and limited fire-fighting resources, which aims to determine the optimal rescue route of fire-fighting teams at multiple rescue centers to minimize the total completion time of all fire-fighting tasks. For this problem, we first assign rescue priorities to different fire points according to the speed of the fire spread. Then, we formulate it into a mixed-integer linear programming (MILP) model and analyze its NP-hard complexity. To deal with large-scale problems, a new fast and effective artificial bee colony algorithm and variable neighborhood search combined algorithm is proposed. Extensive experimental results for large-scale randomly generated instances confirm the favorable performance of the proposed algorithm by comparing it with MILP solver CPLEX, genetic algorithms, and particle swarm optimization algorithms. We also derive some management insights to support emergency management decision-making.
Keyword ：
arti-ficial bee colony algorithm arti-ficial bee colony algorithm emergency scheduling emergency scheduling Forest fires Forest fires MILP MILP variable neighborhood search variable neighborhood search
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| GB/T 7714 | Wang, Lubing , Zhao, Xufeng , Wu, Peng . Resource-Constrained Emergency Scheduling for Forest Fires via Artificial Bee Colony and Variable Neighborhood Search Combined Algorithm [J]. | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS , 2024 , 25 (6) : 5791-5806 . |
| MLA | Wang, Lubing et al. "Resource-Constrained Emergency Scheduling for Forest Fires via Artificial Bee Colony and Variable Neighborhood Search Combined Algorithm" . | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 25 . 6 (2024) : 5791-5806 . |
| APA | Wang, Lubing , Zhao, Xufeng , Wu, Peng . Resource-Constrained Emergency Scheduling for Forest Fires via Artificial Bee Colony and Variable Neighborhood Search Combined Algorithm . | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS , 2024 , 25 (6) , 5791-5806 . |
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