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Collaborative Intelligent Delivery With One Truck and Multiple Heterogeneous Drones in COVID-19 Pandemic Environment

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2024年第7期25卷 7907-7920页

作者： Luo, Yiwen Deng, Xiaoheng Zhang, Wendong Ke, Yan Wan, Shaohua Qian, Yurong Xinjiang Univ Sch Software Urumqi 830001 Peoples R China Cent South Univ Sch Elect Informat Changsha 410083 Peoples R China Shenzhen Res Inst Changsha 410083 Peoples R China Xinjiang Univ Sch Software Urumqi 830001 Peoples R China Univ Elect Sci & Technol China Shenzhen Inst Adv Study Shenzhen 518000 Peoples R China

The outbreak of COVID-19 has caused a serious impact on the traditional logistics industry. Considering that the truck-drone collaborative delivery system can both reduce the risk of COVID-19 propagation and deliver supplies in a cost effective and timely manner, this paper introduces the Multiple visits Travelling Salesman Problem with Multiple Heterogeneous Drones (MTSP-MHD). The model allows a truck to carry a fleet of heterogeneous multi-visit drones for cooperative deliveries, where the drones are capable of delivering to multiple customers on a single route and the flight is restricted by energy consumption and payload constraints. To solve MTSP-MHD, we develop an approach that combines K-Means ++ clustering, Nearest neighbor search and Greedy strategies (KNG) to construct feasible solutions. Meanwhile, an improved artificial bee colony algorithm combining Metropolis acceptance criterion of Simulated Annealing, Tabu list of Tabu Search, and Elite selection strategies (IABC-MTE) is proposed to enhance the quality of solutions. Particularly, three problem-specific neighborhood operators are adopted to search for new solutions. The massive experimental results indicate that IABC-MTE achieves significant improvements over other competitors, with average objective value reductions ranging from 1.81% to 29.16% and standard deviations reduced by 0.04 to 26.44. Finally, the influencing factors of the drone fleet, the performance of different drone fleets and delivery modes are evaluated in detail.

关键词： Drones Payloads Energy consumption Logistics COVID-19 Traveling salesman problems Costs Truck-drone collaborative deliver system multi-visit heterogeneous drones improved artificial bee colony algorithm

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Hearing loss detection by discrete wavelet transform and multi-layer perceptron trained by nature-inspired algorithms

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MULTIMEDIA TOOLS AND APPLICATIONS 2020年第21-22期79卷 15717-15745页

作者： Yang, Jingyuan Govindaraj, Vishnu Varthanan Yang, Ming Wang, Shui-Hua Univ Leicester Dept Informat Leicester LE1 7RH Leics England Kalasalingam Acad Res & Educ Dept Biomed Engn Krishnankoil 626126 Tamil Nadu India Nanjing Med Univ Childrens Hosp Dept Radiol Nanjing 210008 Peoples R China Univ Leicester Dept Math Leicester LE1 7RH Leics England

(Aim) For detecting the hearing loss (HL) more accurately and efficiently, the new computer-aid diagnosis (CAD) based on a nature-inspired algorithm (NIAs) is proposed in this study. (Method) First, the discrete wavelet transform (DWT) is used for extracting texture features from the brain images, and then the principle component analysis (PCA) is employed to decrease the dimension of features. Second, the Multi-Layer Perceptron (MLP) is used as a classifier. Traditional gradient-based descent algorithms are vulnerable to get struck at local minima;thus, the NIAs are introduced. The differential evolution algorithm (DE), particle swarm optimization (PSO), artificial bee colony algorithm (ABC), and improved ABC (IABC) are employed to train MLP. Because the ordinary ABC is good at exploration but gives a poor performance at exploitation, therefore a new model of ABC, called IABC is proposed. The K-fold validation method is utilized to measure the performance of the CAD. (Result) To verify the performance of our method, The CAD based on IABC is compared with state-of-the-art-approaches. (Conclusion) The experiment results show that the overall accuracy of our method has the highest overall accuracy among five approaches. Therefore, the proposed CAD is effective method for detecting hearing loss.

关键词： Hearing loss Computer-aid diagnosis Discrete wavelet transform Multi-layer perceptron Nature-inspired algorithms improved artificial bee colony algorithm K-fold cross validation

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Optimal ECC-based signcryption algorithm for secured video compression process in H.264 encoder

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INTERNATIONAL JOURNAL OF BIOMEDICAL ENGINEERING AND TECHNOLOGY 2020年第1期32卷 36-65页

作者： Rajagopal, Sankarasubbu Shenbagavalli, Ayyachamy Natl Engn Coll Dept Informat Technol Kovilpatti India Natl Engn Coll Dept Elect & Commun Engn Kovilpatti Tamilnadu India

Combination of cryptography method and video technology is a video encryption. Video encryption process is a total and demonstrable security of video data. For the purpose of protecting the video sequence, we have intended to recommend a video compression procedure along with its encryption for providing secured video compression framework. In this document we have suggested a method for ECC-based signcryption algorithm for secured video compression process. At first, encryption process will be used on the motion vector by applying elliptic curve cryptography (ECC)-based signcryption algorithm. The suggested method uses ECC method for the generation of public and private key. At the point when contrasted with the other encryption algorithms like small key, more security, increased velocity, little storage space and low data transfer capacity ECC has particular preferences. The suggested method employs the improved artificial bee colony (IABC) algorithm in order to optimise the private key. Next, the optimal selection of private key applied to encrypt the motion vector. By means of different security attacks such as man in middle (MiM) attack, brute force and denial of service (DoS) attacks, the security of the suggested method will be examined.

关键词： video encryption video compression signcryption elliptic curve cryptography ECC improved artificial bee colony algorithm brute force DoS attack

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Research on Optimization Method for Module Partition Considering Upgrade Risk 3

Research on Optimization Method for Module Partition Conside...

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3rd International Conference on Electronics and Communication;Network and Computer Technology (ECNCT)

作者： Zhang, Qin Pan, Jinlong Hu, Chen Hong, Zhaoxi Feng, Yixiong Huzhou Vocatinal & Tech Coll Key Lab Robot Syst Integrat & Intelligent Equipme Huzhou 313000 Peoples R China Zhejiang Univ State Key Lab Fluid Power & Mechatron Syst Hangzhou 310027 Peoples R China Shanghai Space Prop Technol Res Inst Shanghai 201109 Peoples R China Shanghai Inst Special Equipment Inspect & Tech Re Shanghai 200062 Peoples R China Key Lab Adv Mfg Technol Zhejiang Prov Hangzhou 310027 Peoples R China

ISBN: (数字)9781510652118

ISBN: (纸本)9781510652118;9781510652101

Affected by uncertain factors such as equipment automation transformation and function upgrading, mechanical products may face varying degrees of upgrade risk. In order to solve the problems about high complexity of product upgrading, the optimization method for module partition considering upgrade risk is proposed. Firstly, the basic principles for module partition are analyzed to build fuzzy correlation matrix. With the goal of optimizing module partition quality and minimizing the upgrade complexity, the improved artificial bee colony algorithm is proposed to solve the model. Chaotic dynamic weight factor is introduced to enhance convergence speed of the algorithm. The set of non-dominated solutions for module partition is obtained. Finally, the module partition of an elevator is given to verify the effectiveness of this work.

关键词： optimization upgrade risk module partition improved artificial bee colony algorithm non-dominated solutions

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Parameter identification of proton exchange membrane fuel cell based on swarm intelligence algorithm

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ENERGY 2023年 283卷

作者： Zhang, Bo Wang, Rongjie Jiang, Desong Wang, Yichun Lin, Anhui Wang, Jianfeng Ruan, Bingcong Jimei Univ Sch Marine Engn Xiamen 361021 Peoples R China Fujian Prov Key Lab Naval Architecture & Ocean En Xiamen 361021 Peoples R China 176 Shigu Rd Xiamen 361021 Peoples R China

Accurate estimation of the model parameters of a fuel cell is extremely important to study its system behavior. This paper presents a parameter identification method based on improved artificial bee colony algorithm (IABC). Inspired by the cross operation of genetic algorithm and the cross and mutation operation of differential evo-lution algorithm, this study improves the position update formula of ABC in the parameter optimization process, thus the convergence accuracy and speed of IABC algorithm are improved. The algorithm was used to identify 3 typical standard test cases, namely 250W FC, BCS 500W and NedStack PS6 stack, and the minimum sum of squares (SSE) error between PEMFC measured voltage data and estimated voltage data was defined as the objective function. The SSE values of the three PEMFCs reached 0.29686, 0.011718 and 2.9848, respectively. The model I/V polarization curve estimated by IABC algorithm has a high fitting degree with the experimental measured curve, which indicates the accuracy of IABC algorithm. To verify the superiority of the proposed IABC algorithm, the identification results obtained by some optimization algorithms are compared and ANOVA (analysis of variance) is performed. Results show that the IABC algorithm has faster convergence speed and better robustness.

关键词： Proton exchange membrane fuel cell (PEMFC) improved artificial bee colony algorithm Identification of parameters

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Directional charging-based scheduling strategy for multiple mobile chargers in wireless rechargeable sensor networks

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AD HOC NETWORKS 2023年 149卷

作者： Zhao, Chuanxin Zhu, Pengfei Zhang, Na Chen, Siguang Shao, Xing Wang, Yang Anhui Normal Univ Sch Comp & Informat Wuhu 241002 Peoples R China Nanjing Univ Posts & Telecommun Sch Internet Things Nanjing 210003 Peoples R China Yancheng Inst Technol Sch Informat Engn Yancheng 224051 Peoples R China

With the development of wireless charging technology, the network lifetime of wireless sensor networks has the potential to be significantly extended. Although recent works have explored the use of mobile chargers to charge sensor nodes omnidirectionally, research on directional charging of mobile chargers is lacking. Considering the high efficiency of directional charging, this paper studies mobile charger scheduling using directional charging to achieve node energy replenishment. Initially, charging anchor points and subsets with the highest utility in the network are chosen, enabling a one-to-many directional energy supply. Subsequently, the improved artificial bee colony algorithm is employed to schedule the path planning of multiple mobile chargers. During the charging process, real-time request nodes may be inserted in the planned route, provided that charging time and battery capacity requirements are met. Simulation results demonstrate that the proposed algorithm has advantages over other methods, significantly reducing the moving path length, total energy consumption, and the number of starved nodes.

关键词： Wireless rechargeable sensor networks Path planning Multiple mobile chargers Directional charging improved artificial bee colony algorithm

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Telecommunication Traffic Prediction Based on improved LSSVM

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INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND artificial INTELLIGENCE 2018年第3期32卷 1850007-1850007页

作者： Liu, Jun-Xia Jia, Zhen-Hong Xinjiang Univ Sch Informat Sci & Engn Urumqi 830046 Xinjiang Provin Peoples R China Xinjiang Inst Engn Dept Elect & Informat Urumqi 830023 Xinjiang Provin Peoples R China

Telecommunication traffic prediction is an important aspect of data analysis and processing in communication networks. In this study, we utilize the least-squares support vector machine (LSSVM) prediction method to improve the prediction performance of telecommunication traffic. As the parameters of LSSVM are difficult to determine, we propose to optimize the LSSVM parameters using the improved artificial bee colony (IABC) algorithm based on the fitness-prediction strategy (i.e. FP-IABC). We employ real traffic data collected on site to establish a telecommunication traffic forecasting model based on FP-IABC optimizing LSSVM (FP-IABC-LSSVM). The experiment results indicate that in the case involving no increase in the computational complexity, the proposed telecommunication traffic forecasting model-based FP-IABC-LSSVM has a higher prediction accuracy than the prediction model based on the ABC optimizing LSSVM (ABC-LSSVM), particle swarm optimizing LSSVM (PSO-LSSVM), and genetic algorithm optimizing LSSVM (GA-LSSVM). Further, with respect to the standard root mean square error and the average computation time, the proposed FP-IABC-LSSVM is the optimal prediction method of all of the comparison methods. The proposed prediction method not only improves the prediction accuracy, but also reduces the average computation time.

关键词： Telecommunication traffic prediction least-squares support vector machines improved artificial bee colony algorithm fitness prediction

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Integrated Optimization Approach of Hybrid Flow-Shop Scheduling Based on Process Set

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IEEE ACCESS 2020年 8卷 223782-223796页

作者： Li, Xixing Tang, Hongtao Yang, Zhipeng Wu, Rui Luo, Yabo Hubei Univ Technol Sch Mech Engn Hubei Key Lab Modern Mfg & Qual Engn Wuhan 430068 Peoples R China Wuhan Univ Technol Sch Mech & Elect Engn Hubei Key Lab Digital Mfg Wuhan 430070 Peoples R China

Considering that process planning and production scheduling are independent of each other in a hybrid flow-shop, this study categorizes the process route into parallel process-set, batch set and unordered process-set, and builds a multi-objective optimization model to minimize the maximum completion time and the minimum processing cost. An improved artificial bee colony algorithm has been developed to solve the model. A segmented decoding method based on the insertion principle and the release time of the predecessor process is proposed to effectively use the idle time of the machine. A dynamic triggering neighborhood mechanism is introduced to enhance the local searchabilit of the algorithm. Finally, the feasibility and effectiveness of this algorithm to solve such problems are verified via simulation experiments.

关键词： Job shop scheduling Hafnium Batch production systems artificial bee colony algorithm Heuristic algorithms Manufacturing Optimization Process planning production scheduling hybrid flow-shop improved artificial bee colony algorithm

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Profit Maximization for Service Organizer Based on IABC algorithm

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电脑学刊 2021年第3期32卷 188-209页

作者： Si-Yi Chen Jia-Ling Zhou Si-Ning Huang

In the interaction of service resources among multiple participants, the maximization of profit is always the most concerned fundamental expectation of these participants. However, their expectations can hardly be satisfied simultaneously for the reason of the contradictions and conflicts that existed in their interest demands. In this paper, the interaction between the service organizer and the service provider is discussed in detail. From the perspective of the value of service groups, the value composition and synergy of all participants in science and technology service activities are studied, the service activity process is sorted out, the behavioral characteristics of service entities are analyzed, and the interaction process of interests between service intermediaries and service providers is organized into a mixed-integer linear programming model with constraints. It is determined that the value embodiment in the process of service activities is portrayed by introducing the relevant model of game theory. A game approach is used to describe the mathematical relationships between different service entities in terms of cooperation or non-cooperation. An improved artificial bee colony algorithm is used to solve the problem and promote the multi-party value collaborative optimization of science and technology service activities.

关键词： profit maximization game theory transfer probability improved artificial bee colony algorithm perturbation

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Study on the Control algorithm of Intelligent Greenhouse Crop Precision Planting

Study on the Control Algorithm of Intelligent Greenhouse Cro...

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2016 International Conference on Applied Mechanics,Electronics and Mechatronics Engineering（AMEME 2016）

作者： Ya-lin MIAO Qian XIAO Tian-tian JI XI'an University of Technology

In order to improve the quality of precision cultivation,this paper establishes a control model of precision planting in intelligent greenhouse,and proposes a fuzzy PID control algorithm based on improved artificial bee colony algorithm(IABC-FPID).The optimal parameters combination can be obtained by optimal solution searching in the local parameters *** reduce the possibility of bee system being dropped into local optimum,chaos sequence is introduced to get a target parameter more evenly distributed,thus,it can obtain the optimal control *** simulation results demonstrate that this method has the features of a short setting time,strong stability and high precision,compared to traditional fuzzy PID control.

关键词： Precision planting model Fuzzy PID control improved artificial bee colony algorithm IABC-FPID

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