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Research on the water-ground multimodal transport emergency scheduling model and decision-making method considering the actual road network inundation situation

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RISK ANALYSIS 2025年第3期45卷 600-622页

作者： Song, Yan Sun, Baiqing Han, Yunwu Xing, Zhenming Harbin Inst Technol Sch Management Harbin 150001 Peoples R China Jiangsu Vocat Coll Elect & Informat Dept Automobile Engn Huaian Peoples R China Harbin Inst Technol State Key Lab Robot & Syst Harbin Peoples R China

As urbanization continues to accelerate worldwide, urban flooding is becoming increasingly destructive, making it important to improve emergency scheduling capabilities. Compared to other scheduling problems, the urban flood emergency rescue scheduling problem is more complicated. Considering the impact of a disaster on the road network passability, a single type of vehicle cannot complete all rescue tasks. A reasonable combination of multiple vehicle types for cooperative rescue can improve the efficiency of rescue tasks. This study focuses on the urban flood emergency rescue scheduling problem considering the actual road network inundation situation. First, the progress and shortcomings of related research are analyzed. Then, a four-level emergency transportation network based on the collaborative water-ground multimodal transport transshipment mode is established. It is shown that the transshipment points have random locations and quantities according to the actual inundation situation. Subsequently, an interactive model based on hierarchical optimization is constructed considering the travel length, travel time, and waiting time as hierarchical optimization objectives. Next, an improved A* algorithm based on the quantity of specific extension nodes is proposed, and a scheduling scheme decision-making algorithm is proposed based on the improved A* and greedy algorithms. Finally, the proposed decision-making algorithm is applied in a practical example for solving and comparative analysis, and the results show that the improved A* algorithm is faster and more accurate. The results also verify the effectiveness of the scheduling model and decision-making algorithm. Finally, a scheduling scheme with the shortest travel time for the proposed emergency scheduling problem is obtained.

关键词： emergency rescue greedy algorithm improved A* algorithm scheduling scheme decision-making urban flooding water-ground multimodal transport

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greedy algorithm Based Deformable Simplex Meshes Using Gradient Vector Flow as External Energy 7

Greedy Algorithm Based Deformable Simplex Meshes Using Gradi...

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7th International Conference on Biomedical Engineering and Informatics (BMEI)

作者： Shi, Changfa Guo, Changyong Cheng, Yuanzhi Wang, Jinke Harbin Inst Technol Sch Comp Sci & Technol Harbin 150006 Peoples R China Harbin Univ Sci & Technol Software Engn Dept Rongcheng Coll Rongcheng Peoples R China

ISBN: (纸本)9781479958382

Deformable models have been quite popular in medical image analysis, particularly in image segmentation. However, when applied to 3D volumetric data, their high computational cost can be a problem. In this paper, we describe a new efficient 3D segmentation method based on deformable simplex meshes. The greedy algorithm, which has proven more computational efficient and robust than physics-based method, is employed to perform the shape deformation. Generalized gradient vector flow (GGVF) field is a classical external force for physics-based deformable models. We adapt it for greedy algorithm as external energy to overcome the main issues of the traditional external energy (i.e., sensitivity to shape initialization and poor convergence to the long and thin boundary concavities). Results of applying our method to both synthetic and clinical images are presented to illustrate the accuracy and robustness of our proposed method.

关键词： Deformable models simplex meshes greedy algorithm GGVF energy

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The integrated planning of outgoing coil selection for retrieval, multi-crane scheduling, and location assignment to the incoming and blocking coils in steel coil warehouses

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COMPUTERS & INDUSTRIAL ENGINEERING 2024年 190卷

作者： Nadali, Fatemeh Iranpoor, Mehdi Malekian, Yaser Isfahan Univ Technol Dept Ind & Syst Engn Esfahan *** Iran

In this paper, the problem of scheduling crane -operated warehouses in a triangle stacking style is investigated. In a steel supply chain, warehouses play a significant role in establishing a connection between the producer and the customers. Therefore, improving their performance results in a competitive advantage in the supply chain. One of the challenges of steel coil warehouses is the selection of outgoing coils out of the candidate coils for retrieval. Despite its importance, this problem has not been investigated in the studies relevant to steel coil warehouses. In this study, in addition to the selection of outgoing coils, sequencing of the operations on the incoming, outgoing, and blocking coils, location assignment to the incoming and blocking coils, and crane scheduling are considered in an integrated manner. First, a mixed integer linear programming model is proposed. Further, a greedy heuristic algorithm and two metaheuristics are developed to solve large -sized instances of the problem. Metaheuristics include a greedy Randomized Adaptive Search Procedure (GRASP) and a hybrid algorithm that combines Ant Colony System with the GRASP (ACS -GRASP). Finally, performances of the proposed algorithms are compared over randomly generated instances as well as instances which are generated based on the real data obtained from Isfahan's Mobarakeh Steel Company. To conduct this analysis, various performance evaluation metrics are applied. Computational results indicate that ACS -GRASP converges slower than GRASP, but is more reliable and efficient. On the other hand, in large -sized instances, the greedy algorithm runs extremely fast and can find solutions which are comparable to the metaheuristic solutions.

关键词： Multi-crane scheduling greedy algorithm GRASP algorithm Ant colony system algorithm Outgoing coil selection

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Selector of amino-acid scales set

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MATHEMATICAL MEDICINE AND BIOLOGY-A JOURNAL OF THE IMA 2024年第3期41卷 157-168页

作者： Vrdoljak, Anton Vukicevic, Damir Univ Mostar Fac Civil Engn Architecture & Geodesy Mostar 88000 Bosnia & Herceg Univ Split Fac Sci Dept Math Rudera Boskovica 33 Split 21000 Croatia

Experimental and theoretical properties of amino acids as building blocks of peptides and proteins have been extensively researched. Each such method assigns a number to each amino acid, and one such assignment is called amino-acid scale. Their usage in bioinformatics to explain and predict behaviour of peptides and proteins is of essential value. The number of such scales is very large. There are more than a hundred scales related just to hydrophobicity. A large number of scales can be a computational burden for algorithms that try to define peptide descriptors combining several of these scales. Hence, it is of interest to construct a smaller, but still representative set of scales. Here, we present software that does this. We test it on the set of scales using a database constructed by Kawashima and collaborators and show that it is possible to significantly reduce the number of scales observed without losing much of the information. An algorithm is implemented in C#. As a result, we provide a smaller database that might be a very useful tool for the analyses and construction of new peptides. Another interesting application of this database would be to compare the artificial intelligence construction of peptides having as an input the complete Kawashima database and this reduced one. Obtaining in both cases similar results would give much credibility to the constructs of such AI algorithms.

关键词： amino-acid scales peptide analysis tool dominating set greedy algorithm variable neighborhood search

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A greedy particle swarm optimization (GPSO) algorithm for testing real-world smart card applications

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INTERNATIONAL JOURNAL ON SOFTWARE TOOLS FOR TECHNOLOGY TRANSFER 2020年第2期22卷 183-194页

作者： Allawi, Hamzeh M. Al Manaseer, Waref Al Shraideh, Mohammad Univ Jordan Dept Comp Sci Amman Jordan

Software testing continues to be regarded as a necessary and critical step in the software development life cycle. Among the multitudes of existing techniques, particle swarm optimization (PSO) algorithm, in particular, has shown superior merits for automatically generating software test cases for its easy implementation and for relying on fewer parameters that require tuning. Hence, several state-of-the-art PSO-based algorithms have been successfully used as a test data generator. On the other hand, greedy-based algorithms, which are commonly used to solve complex and multi-step combinatorial problems, are starting to gain momentum as a solution for the complexity problem of software testing. greedy algorithms favored over other techniques when the solution of the problem is guaranteed to be near-optimal. As a result, the utilization of both greedy and PSO algorithms in a single solution for automatically generating test data represents a strong candidate if designed carefully. In this paper, we propose a novel hybrid greedy and PSO algorithm (GPSO) that jointly guarantees the effectiveness and close to optimality results for generating a minimum number of test data. Compared with the widely employed genetic algorithm (GA), our proposed GPSO outperforms the GA in terms of the average number of iterations, execution time, and coverage percentage. Experimental trials with six different typical Java card applications show that the use of the proposed GPSO as a test data generator results in an outstanding performance.

关键词： Software testing Java smart card Particle swarm optimization algorithm greedy algorithm Genetic algorithm

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Hartree-Fock approximation for bosons with symmetry-adapted variational wave functions

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PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 2025年 664卷

作者： Que, B. R. Zhang, J. M. Song, H. F. Liu, Y. Fujian Normal Univ Coll Phys & Energy Fujian Prov Key Lab Quantum Manipulat & New Energy Fuzhou Peoples R China Fujian Prov Collaborat Innovat Ctr Optoelect Semic Xiamen Peoples R China Inst Appl Phys & Computat Math Lab Computat Phys Beijing Peoples R China

The Hartree-Fock approximation for bosons employs variational wave functions that are a combination of permanents. These are bosonic counterpart of the fermionic Slater determinants, but with the significant distinction that the single-particle orbitals used to construct a permanent can be arbitrary and do not need to be orthogonal to each other. Typically, the variational wave function may break the symmetry of the Hamiltonian, resulting in qualitative and quantitative errors in physical observables. A straightforward method to restore symmetry is projection after variation, where we project the variational wave function onto the desired symmetry sector. However, a more effective strategy is variation after projection, which involves first creating a symmetry-adapted variational wave function and then optimizing its parameters. We have devised a scheme to realize this strategy and have tested it on various models with symmetry groups ranging from Z2, CL, to DL. In all the models and symmetry sectors studied, the variational wave function accurately estimates not only the energy of the lowest eigenstate but also the single-particle correlation function, as it approximate the target eigenstate very well on the wave function level. We have applied this method to study few-body bound states, superfluid fraction, and Yrast lines of some Bose-Hubbard models. This approach should be valuable for studying few-body or mesoscopic bosonic systems.

关键词： Hartree-Fock Variational wave function Permanent state Variation after projection greedy algorithm Bose-Hubbard model

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Edge Caching Data Distribution Strategy with Minimum Energy Consumption

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SENSORS 2024年第9期24卷 2898页

作者： Lin, Zhi Liang, Jiarong Guangxi Univ Sch Comp Elect & Informat Nanning 530004 Peoples R China

In the context of the rapid development of the Internet of Vehicles, virtual reality, automatic driving and the industrial Internet, the terminal devices in the network show explosive growth. As a result, more and more information is generated from the edge of the network, which makes the data throughput increase dramatically in the mobile communication network. As the key technology of the fifth-generation mobile communication network, mobile edge caching technology which caches popular data to the edge server deployed at the edge of the network avoids the data transmission delay of the backhaul link and the occurrence of network congestion. With the growing scale of the network, distributing hot data from cloud servers to edge servers will generate huge energy consumption. To realize the green and sustainable development of the communication industry and reduce the energy consumption of distribution of data that needs to be cached in edge servers, we make the first attempt to propose and solve the problem of edge caching data distribution with minimum energy consumption (ECDDMEC) in this paper. First, we model and formulate the problem as a constrained optimization problem and then prove its NP-hardness. Subsequently, we design a greedy algorithm with computational complexity of O(n2) to solve the problem approximately. Experimental results show that compared with the distribution strategy of each edge server directly requesting data from the cloud server, the strategy obtained by the algorithm can significantly reduce the energy consumption of data distribution.

关键词： mobile edge computing edge caching green communication mobile communication greedy algorithm

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Influence maximization in mobile social networks based on RWP-CELF

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COMPUTING 2024年第6期106卷 1913-1931页

作者： Xu, Zhenyu Zhang, Xinxin Chen, Mingzhi Xu, Li Fujian Normal Univ Coll Comp & Cyber Secur Fuzhou Fujian Peoples R China Fujian Normal Univ Fujian Prov Key Lab Network Secur & Cryptol Fuzhou Fujian Peoples R China Henan Univ Technol Sch Artificial Intelligence & Big Data Zhengzhou Peoples R China

Influence maximization (IM) problem for messages propagation is an important topic in mobile social networks. The success of the spreading process depends on the mechanism for selection of the influential user. Beside selection of influential users, the computation and running time should be considered in this mechanism to ensure the accurecy and efficient. In this paper, considering that the overhead of exact computation varies nonlinearly with fluctuations in data size, random algorithm with smoother complexity change was designed to solve the IM problem in combination with greedy algorithm. Firstly, we proposed a method named two-hop neighbor network influence estimator to evaluate the influence of all nodes in the two-hop neighbor network. Then, we developed a novel greedy algorithm, the random walk probability cost-effective with lazy-forward (RWP-CELF) algorithm by modifying cost-effective with lazy-forward (CELF) with random algorithm, which uses 25-50 orders of magnitude less time than the state-of-the-art algorithms. We compared the influence spread effect of RWP-CELF on real datasets with a theoretically proven algorithm that is guaranteed to be approximately optimal. Experiments show that the spread effect of RWP-CELF is comparable to this algorithm, and the running time is much lower than this algorithm.

关键词： Influence maximization Mobile social network Two-hop neighbor network influence estimator Random algorithm greedy algorithm 9103D

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Data-driven trafflc sensor location and path flow estimation using Wasserstein metric

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APPLIED MATHEMATICAL MODELLING 2024年 133卷 211-231页

作者： Gao, Jiaqi Yang, Kai Shen, Mengru Yang, Lixing Beijing Jiaotong Univ Sch Syst Sci Beijing 100044 Peoples R China Beijing Jiaotong Univ Sch Traff & Transportat Beijing 100044 Peoples R China

This paper introduces link information value obtained by the trafflc sensors and presents a trafflc sensor location and flow estimation joint optimization model in an urban road network. In contrast to most previous studies, this paper adds new trafflc sensors into the existing sensor network and proposes a data-driven path flow measurement method based on Wasserstein metric, which is utilized to measure the distance between the estimated trafflc flow distribution and the actual distribution. Furthermore, this paper develops a customized greedy algorithm by combining a search strategy for the link information value to obtain the optimal sensor location scheme and perform trafflc flow estimation under different budget conditions. Numerical experiments are conducted on Sioux-Falls test network and Eastern Massachusetts interstate highway subnetwork to verify the accuracy and effectiveness of the proposed model based on Wasserstein metric and the developed solution method. Computational results show that the sensor location scheme generated by the model based on Wasserstein metric can reduce the estimation error of the trafflc flow compared with KL divergence model under the same deployment cost. Additionally, the customized greedy algorithm can achieve the better performance than the Brute force algorithm in terms of computing time and solution quality.

关键词： Transportation planning Sensor location Wasserstein metric Flow estimation greedy algorithm

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The sum of root-leaf distance interdiction problem with cardinality constraint by upgrading edges on trees

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JOURNAL OF COMBINATORIAL OPTIMIZATION 2024年第5期48卷 1-30页

作者： Li, Xiao Guan, Xiucui Zhang, Qiao Yin, Xinyi Pardalos, Panos M. Southeast Univ Sch Math Nanjing 210096 Jiangsu Peoples R China Changzhou Univ Aliyun Sch Big Data Changzhou 213164 Jiangsu Peoples R China Univ Florida Ctr Appl Optimizat Dept Ind & Syst Engn Gainesville FL USA

A network for the transportation of supplies can be described as a rooted tree with a weight of a degree of congestion for each edge. We take the sum of root-leaf distance (SRD) on a rooted tree as the whole degree of congestion of the tree. Hence, we consider the SRD interdiction problem on trees with cardinality constraint by upgrading edges, denoted by (SDIPTC). It aims to maximize the SRD by upgrading the weights of N critical edges such that the total upgrade cost under some measurement is upper-bounded by a given value. The relevant minimum cost problem (MCSDIPTC) aims to minimize the total upgrade cost on the premise that the SRD is lower-bounded by a given value. We develop two different norms including weighted l(infinity) norm and weighted bottleneck Hamming distance to measure the upgrade cost. We propose two binary search algorithms within O(nlog n) time for the problems (SDIPTC) under the two norms, respectively. For problems (MCSDIPTC), we propose two binary search algorithms within O(Nn(2)) and O(nlog n) under weighted l(infinity) norm and weighted bottleneck Hamming distance, respectively. These problems are solved through their subproblems (SDIPT) and (MCSDIPT), in which we ignore the cardinality constraint on the number of upgraded edges. Finally, we design numerical experiments to show the effectiveness of these algorithms.

关键词： Network interdiction problems Tree greedy algorithm Binary search method l(infinity) norm Bottleneck Hamming distance

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