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Does the minimization of the average vehicle delay and the minimization of the average number of stops mean the same at the signalized intersections?

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International Journal of Transportation Science and Technology 2024年第1期13卷 213-228页

作者： Ziya Cakici Goker Aksoy Izmir Democracy University Faculty of EngineeringDepartment of Civil Engineering35140IzmirTürkiye Gebze Technical University Institution of Transportation Technologies41400 GebzeKocaeliTürkiye

Signal timings at signalized intersections are frequently optimized by considering com monlyusedvehicle delay *** is generally believed that reducing the average number of stops can also decrease the average vehicle ***,the aim of this research is to address the question:“Can similar performance outcomes be achieved through the Minimization of Average Vehicle Delay(MAVD)and the Minimization of Average Number of Stops(MANS)?”The first phase of the study entails the creation of two distinct signal timing optimization models based on the Akcelik average vehicle delay and average number of stops ***,scripts were developed in MATLAB to identify the optimal signal timings for both approaches utilizing the differential evolution *** the third phase,30 traffic scenarios were generated,each varying in overall traffic vol umes at the ***,the signal timings derived from the MAVD and MANSapproaches were applied independently to these scenarios,and performance indica tors(average vehicle delay and average number of stops)were *** results reveal that the utilization of MANS-based signal timings instead of MAVD may lead to an increase in average vehicle delays of up to 113.55%.Additionally,it is demonstrated that when MAVD-based signal timings are applied instead of MANS,the average number of stops can increase by up to 16.28%.Finally,it is concluded that as the overall traffic volume at the intersection increases,these growth rates tend to decrease.

关键词： Signalized intersection Average vehicle delay Average number of stops differential evolution algorithm Optimization

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Utilization of data and information flows for enhancing a chambermaid scheduling decision making in a smart hospitality supply chain

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ANNALS OF OPERATIONS RESEARCH 2024年第1期335卷 639-639页

作者： Pitakaso, Rapeepan Sethanan, Kanchana Worasan, Kongkidakhon Golinska-Dawson, Paulina Ubon Ratchathani Univ Fac Engn Dept Ind Engn Artificial Intelligence Optimizat SMART Lab Ubon Ratchathani Thailand Khon Kaen Univ Fac Engn Dept Ind Engn Res Unit Syst Modelling Ind Khon Kaen 40002 Thailand Khon Kaen Univ Fac Business Adm & Accountancy Khon Kaen 40002 Thailand Poznan Univ Tech Fac Engn Management 2 Jacka Rychlewskiego Str PL-60965 Poznan Poland

This study presents a novel approach for chambermaid scheduling that integrates data and information flows through mobile applications and a technique called variable neighborhood strategy adaptive search (VaNSAS). VaNSAS employs two simple heuristics, moving network method (MNM) and simple neighborhood search routine (SNSR), along with a simplified differential evolution (SDE) to create schedules. The study demonstrates the effectiveness of the proposed approach, which outperforms traditional manual methods. The use of VaNSAS results in an average improvement of 184.39% in finding better solutions, a reduction in scheduling time by 175.78%, an enhancement in load balancing among chambermaids by 94.25%, and a productivity increase by 50%. The results contribute to improving overall efficiency in the hotel business by facilitating workforce management and demand uncertainties, reducing workload, enabling control of work duration, and enhancing customer satisfaction by allowing customers to better manage their daily schedules. The integration of data and information flows with VaNSAS for chambermaid scheduling has the potential to revolutionize the hospitality sector. In order to facilitate decision-making for the allocation and scheduling of chambermaids, an Internet of Things integrated chambermaid allocation and scheduling software is adopted, which provides a more efficient approach.

关键词： Hotel industry Chambermaid allocation scheduling VaNSAS Mobile apps in hotel industry Moving network method differential evolution algorithm

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High-speed train positioning based on a combination of Beidou navigation, inertial navigation and an electronic map

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Science China(Information Sciences) 2023年第7期66卷 237-252页

作者： Hui YANG Shuai-Qiang DONG Chun-Hua XIE School of Electrical and Automation Engineering East China Jiaotong University Key Laboratory of Advanced Control & Optimization of Jiangxi Province East China Jiaotong University State Key Laboratory of Performance Monitoring Protecting of Rail Transit Infrastructure East China Jiaotong University

To date, the studies on the combination positioning of high-speed trains have made great progress, but the positioning accuracy of these methods is relatively low. Map-matching positioning can improve positioning accuracy, but information transmission is time-consuming. Few studies incorporate it into combination positioning. To solve the problem, this paper proposes a high-speed train positioning method based on combining a Beidou navigation system, an inertial navigation system, and an electronic map. First, the combination positioning problem is transformed into a multi-objective optimization problem, which weights the direction similarity and distance error to form a fitness function and converts the railway line and the maximum error range of each positioning system into constraints. Second, an improved differential evolution algorithm is proposed to solve this problem. By referencing the gray wolf algorithm,the differential evolution algorithm updates individuals by varying toward the direction of multiple optimal values. Then, a new combination positioning algorithm for high-speed trains is proposed. In the simulation,the increase in positioning speed and accuracy is analyzed and validated. Compared to the current algorithms, the proposed algorithm performs better. The proposed method has practical value for improving the reliability and safety of train operations.

关键词： electronic map multi-objective optimization differential evolution algorithm Beidou navigation system high-speed train positioning

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Numerical Simulation of Cyclic Degradations of Reinforced Concrete Columns: Model Parameter Calibration and Experimental Validation

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JOURNAL OF EARTHQUAKE ENGINEERING 2025年第6期29卷 1356-1375页

作者： Zhou, Xun Li, Jianzhong Yin, Kangshuai Tongji Univ State Key Lab Disaster Reduct Civil Engn Shanghai 200092 Peoples R China

This study focuses on the numerical simulation of significant cyclic degradations for reinforced concrete columns. For both accuracy and computational efficiency, the modified Ibarra-Medina-Krawinkler model was adopted for the simulation. The parameters controlling the model were obtained through a novel calibration procedure based on a database containing 183 rectangular columns exhibiting flexural or flexural-shear failure. Regression analyses were employed to develop explicit predictive equations for the calibrated parameters. Further, quasi-static experiments were conducted on three reinforced concrete columns. The applicability and accuracy of the predictive equations were demonstrated by comparison with the experimental results.

关键词： Reinforced concrete columns cyclic degradation model calibration differential evolution algorithm predictive equation

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DEAttack: A differential evolution based attack method for the robustness evaluation of medical image segmentation

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NEUROCOMPUTING 2021年 465卷 38-52页

作者： Cui, Xiangxiang Chang, Shi Li, Chen Kong, Bin Tian, Lihua Wang, Hongqiang Huang, Peng Yang, Meng Wu, Yenan Li, Zhongyu Xian Fiaotong Univ Sch Software Engn Xian Peoples R China Cent South Univ Dept Gen Surg Xiangya Hosp Changsha Peoples R China Univ N Carolina Dept Comp Sci Charlotte NC USA Frontline Intelligent Technol Nanjing Co Ltd Nanjing Peoples R China

Deep learning is an effective tool to assist doctors with many time-consuming and error-prone medical image analytical tasks. However, deep models are shown to be vulnerable to adversarial attacks, posing significant challenges to clinical applications. Existing works regarding the robustness of deep learning models are scarce, where most of them focus on the attack of medical image classification models. In this paper, a differential evolution attack (DEAttack) method is proposed to generate adversarial examples for medical image segmentation models. Our method does not require extra information such as the net-work's structures and weights compared with the most widely investigated gradient-based attack meth-ods. Additionally, benefit from the embedded differential evolution algorithm, which can preserve diversities of the optimization space. The proposed method can achieve better results than gradient -based methods, which can successfully attack the segmentation model with only perturbing a small frac-tion of the image pixels, demonstrating that the medical image segmentation model is more susceptible to adversarial examples. In addition to evaluating model robustness attack with public datasets, our DEAttack method was also tested on the clinical diagnostic dataset, demonstrating its superior perfor-mance and elegant process for the robustness evaluation of deep models in medical image segmentation. (c) 2021 Elsevier B.V. All rights reserved.

关键词： Medical image segmentation Adversarial attack differential evolution algorithm Robustness evaluation

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Synthesis of Distributed Array Consisting of Two Subarrays via Hybrid Method of differential evolution Optimization and Convex Optimization

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IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS 2021年第2期20卷 125-129页

作者： Fang, Shutao Li, Weiming Xue, Zhenghui Ren, Wu Beijing Inst Technol Beijing 100081 Peoples R China Beijing Inst Technol Sch Informat & Elect Beijing 100081 Peoples R China Beijing Inst Technol EMC & Microwave Syst Lab Beijing 100081 Peoples R China

In this letter, we present a hybrid optimization method for the synthesis of distributed array consisting of two identical subarrays, which is mainly used on aeroplanes as the front end of communication system, aiming to lower the grating lobe level as much as possible. The proposed method is on the basis of a combination of differential evolution optimization and weighted l(1) convex optimization. In the procedure of optimization, a hybrid method of optimization is proposed to optimize element positions and excitations to obtain the optimum performance, while multiple constraints are adopted to satisfy the application requirements. Numerical comparisons between different values of parameters are presented to assess the effectiveness of the proposed optimization method, showing the best result of optimization possibly obtained with different parameters.

关键词： Convex optimization differential evolution algorithm distributed array synthesis grating lobe suppression

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Configuration design and dimensional synthesis of an asymmetry 2R1T parallel mechanism

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ROBOTICA 2023年第2期41卷 713-734页

作者： Peng, Siyang Cheng, Zhihong Che, Linxian Cui, Song Jin, Zujin China Univ Min & Technol Sch Mechatron Engn Xuzhou 221116 Jiangsu Peoples R China Chongqing Vocat Inst Engn Sch Intelligence Mfg & Traff Chongqing 402260 Peoples R China

This paper focuses on configuration design, dimensional synthesis, and engineering application of a novel asymmetric 2R1T parallel mechanism (PM) with zero-coupling degree. The analytical forward and inverse displacement solutions are deduced by the means of vector method. The mathematical models between Euler angles and the orientational parameters (i.e., azimuth and tilt angles) of the offset output axis are established. Using screw theory as mathematical tool, this paper worked out evaluation indices of motion/force transmissibility and presented the definitions and calculation methods of good transmission orientation workspace and good transmission orientation capacity (GTOC). Furthermore, a comparative example with respect to kinematic performance of asymmetric UPS-RPU-PU PM and planar symmetric 2UPS-PU PM is carried out, and the result demonstrates that UPS-RPU-PU significantly outperforms 2UPS-PU in terms of GTOC. The constrained optimization model is constructed to formulate optimal problem of dimensional parameters on the maximizing GTOC, which is then solved by differential evolution algorithm. Finally, an engineering case demonstrates that the optimized mechanism has a good application prospect in hydraulic support test bed.

关键词： parallel mechanism dimensional optimization design transmissibility evaluation index good transmission orientation capacity differential evolution algorithm hydraulic support test bed

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Gravity assist space pruning and global optimization of spacecraft trajectories for solar system boundary exploration

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COMPLEX & INTELLIGENT SYSTEMS 2024年第1期10卷 323-341页

作者： Song, Yuqi Wu, Weiren Hu, Hang Lin, Mingpei Wang, Hui Zhang, Jinxiu Sun Yat Sen Univ Sch Phys & Astron Zhuhai 519082 Peoples R China Lunar Explorat & Space Engn Ctr Beijing 100037 Peoples R China Sun Yat Sen Univ Sch Aeronaut & Astronaut Shenzhen 518107 Peoples R China

The solar system boundary exploration mission has the characteristics of long flight time, high fuel consumption, complex gravity-assist sequence and strict constraints. Therefore, the number of decision variables and the search space of the transfer trajectory are very large, resulting in poor convergence and efficiency of the global search of the metaheuristic algorithm. Moreover, the existing gravity assist space pruning algorithm is no longer applicable for solar system boundary exploration. To effectively reduce the search space and improve the effect of trajectory optimization, an improved gravity assist space pruning algorithm is proposed. In this algorithm, a unique pruning procedure is used to effectively prune the search space, a shape of solution space box bounds combining rectangle and rhombus is adopted, and a method to automatically determine the solution space box bounds is presented. To verify the effectiveness of the improved gravity assist space pruning algorithm, the sensitivity of pruning effect to parameters is analyzed and the optimization effects of three typical metaheuristics are compared. The optimization results of 50 repeated runs of the differential evolution algorithm in the entire search space and the solution space box bounds are compared. Simulation results show that the performance of differential evolution algorithm is better than bat algorithm and firefly algorithm. And the improved pruning algorithm can increase the efficiency of subsequent optimization by more than eleven times and the convergence probability of the objective function by fifty of times. The applicability and efficiency of the proposed method for the solar system boundary exploration are demonstrated.

关键词： Solar system boundary exploration Global optimization of transfer trajectory differential evolution algorithm Gravity assist space pruning Solution space box bounds

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Back analysis of rock mass parameters in tunnel engineering using machine learning techniques

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COMPUTERS AND GEOTECHNICS 2023年第1期163卷

作者： Chang, Xiangyu Wang, Hao Zhang, Yiming Southeast Univ Key Lab C&PC Struct Minist Educ Nanjing 211189 Jiangsu Peoples R China Nanyang Technol Univ Sch Civil & Environm Engn Nanyang Singapore Univ Cambridge Dept Engn Cambridge England

Efficient determination of the rock mass properties is vitally important for calculating and evaluating tunnel stability in tunnel engineering. The back analysis method has been widely used as an indirect method for determining rock mass parameters based on field measurements. However, most back analysis methods are generally time-consuming for numerical simulation and are merely based on the measured displacement, which leads to the identification of rock mass parameters that cannot fully reflect the characteristics of the surrounding rock. To improve the accuracy of the estimation of rock mass parameters, this paper presents a back analysis method based on multi-output support vector regression (MSVR) and differential evolution (DE) algorithms. Firstly, the global sensitivity analysis of rock mass parameters is analyzed using the elementary effects method. Numerical simulation is then carried out to prepare training samples. DE algorithm is used to determine the optimum hyperparameters of MSVR. Based on the monitoring data, the rock mass properties of the selected sensitive parameters are estimated by the constructed MSVR model. A high-speed railway tunnel is utilized to demonstrate the effectiveness of the MSVR with the DE algorithm (DE-MSVR). The results show that the DE-MSVR with mixed monitoring data of vault settlement, convergence, and rock mass stress has higher fore-casting performance than these models with a single type of monitoring data. It is feasible to use the monitoring data at the early stages combined with the numerical simulation for parameter back analysis. Moreover, the comparison results show that the presented method exhibits higher prediction accuracy than the existing back analysis models.

关键词： Tunnel engineering Back analysis technique Rock mass properties differential evolution algorithm Multi -output support vector regression

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An application of artificial intelligence for solving multi-visit scheduling and routing of multi-heterogeneous resources

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ANNALS OF OPERATIONS RESEARCH 2024年 1-50页

作者： Pitakaso, Rapeepan Sethanan, Kanchana Kumar, Ajay Tan, Kim Hua Nanthasamroeng, Natthapong Ubon Ratchathani Univ Fac Engn Dept Ind Engn Metaheurist Logist Optimizat Lab Ubon Ratchathani Thailand Khon Kaen Univ Fac Engn Dept Ind Engn Res Unit Syst Modelling Ind Khon Kaen 40002 Thailand EMLYON Business Sch Dept Operat Data & Artificial Intelligence Ecully France Univ Nottingham Business Sch Nottingham England Ubon Ratchathani Rajabhat Univ Fac Ind Technol Ubon Ratchathani Thailand

This research focuses on the development of an artificial multiple intelligence system (AMIS) for solving multi-visit scheduling and routing of multi-heterogeneous resources. The proposed method has been developed as a decision-making tool for solving mechanical sugarcane harvest operations which have been replacing the manual harvesting system with the sugarcane field burning. The mechanical sugarcane harvesting system is a fresh one with a high potential reduction of CO2 emission. Two resources which are fuel service staff teams and technician teams were considered to support the mechanical harvester operations in order to improve the harvesters' productivity and stability of its sugarcane supply by minimizing the downtime or waiting time of harvesters. Based on this approach, not only the sugar production is efficient, but also the harvesting which is the inbound activity is fuel-efficient. This problem was formulated as the allocation and scheduling of multi-Heterogeneous Resources with consideration of transportation for both resources and service operations. Sugarcane harvesters which get services from the workforce are geographically scattered in each time period. There are various technicians and fuel service staff with different skills giving services to the harvesters. The workforce allocation (WFAllcn) and the sequences and routing (WFSeqRoute) sub-problems were modeled as the integrating problem with the objective function to maximize the sugarcane harvested by all harvesters. To solve the problem, the Artificial Multiple Intelligence System (AMIS), which was developed with new intelligence box selection rules, is firstly developed. Using this approach, allocation and scheduling, and routing of technicians and fuel service staff in sugarcane mechanical harvest operations is very efficient.

关键词： Sugarcane harvesting Multi-visit scheduling and routing Optimization differential evolution algorithm

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