Article
Management
Cheng Chen, Emrah Demir, Yuan Huang
Summary: This paper investigates the routing and scheduling of autonomous delivery robots in urban logistics, proposing an algorithm to solve the VRPTWDR and demonstrating its performance and effectiveness. The research shows that self-driving parcel delivery robots can be a new alternative for last mile service.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Computer Science, Information Systems
Yiqiao Cai, Meiqin Cheng, Ying Zhou, Peizhong Liu, Jing-Ming Guo
Summary: In this study, a hybrid evolutionary multitask algorithm (HEMT) is proposed to solve multiobjective vehicle routing problems with time windows (MOVRPTWs). The algorithm simultaneously optimizes multiple similar MOVRPTWs by globally exploring the search space, conducting local searches, and reusing problem-specific knowledge. Experimental results demonstrate the effectiveness and superiority of the proposed algorithm.
INFORMATION SCIENCES
(2022)
Article
Computer Science, Interdisciplinary Applications
Wenqiang Zhang, Haoran Li, Weidong Yang, Guohui Zhang, Mitsuo Gen
Summary: This study proposes a hybrid multiobjective evolutionary algorithm based on combination timing to solve the multi-type vehicle routing problem with time windows. The algorithm combines global search and local search in different evolutionary stages to achieve the goal of minimizing the number of vehicles and wasting time simultaneously.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Computer Science, Information Systems
Rui Qi, Jun-qing Li, Juan Wang, Hui Jin, Yu-yan Han
Summary: This study introduces a time-dependent green vehicle routing problem and proposes a Q-learning-based multiobjective evolutionary algorithm to solve the problem. The algorithm considers three objectives: total duration of vehicles, energy consumption, and customer satisfaction. It utilizes a hybrid initial method and Pareto-front-based crossover strategies to improve search efficiency.
INFORMATION SCIENCES
(2022)
Article
Computer Science, Information Systems
Meiling He, Zhixiu Wei, Xiaohui Wu, Yongtao Peng
Summary: An adaptive variable neighborhood search ant colony algorithm (AVNSACA) is proposed to solve the VRPSTW problem, which improves the pheromone update strategy and designs variable neighborhood search operators to avoid the algorithm falling into local optima. Experimental results demonstrate the effectiveness of the AVNSACA in obtaining better solutions for vehicle routing with soft time windows.
Article
Computer Science, Artificial Intelligence
Shengcai Liu, Ke Tang, Xin Yao
Summary: The novel Memetic Algorithm MATE is proposed in this paper to solve the Vehicle Routing Problem with Simultaneous Pickup-Delivery and Time Windows. It outperforms existing algorithms by effectively exploring the search space and being more efficient in local exploitation, as demonstrated by experimental results and analysis.
SWARM AND EVOLUTIONARY COMPUTATION
(2021)
Article
Engineering, Civil
Xiaojian Yuan, Qishan Zhang, Jiaoyan Zeng
Summary: This study investigates the impact of grey delivery time uncertainty on customer satisfaction and delivery costs by defining a vehicle routing problem with grey delivery time windows and multiobjective constraints. Experimental results show that the grey time windows have certain advantages in solving the random travel time vehicle routing problem using an improved quantum evolution algorithm.
JOURNAL OF ADVANCED TRANSPORTATION
(2021)
Article
Operations Research & Management Science
Fatemeh Zandieh, Seyed Farid Ghannadpour
Summary: Hazardous material transportation is an integral part of the industry with significant financial and health risks. A multi-objective Hazmat routing model with time windows is used to optimize transportation, minimizing both risk and distance. To handle the uncertainty of Hazmat transportation risk, a Z-number fuzzy approach is applied, considering the probability of occurrence and severity. A multi-objective hybrid genetic algorithm is used to solve the proposed model, which is validated using Solomon's problems. The efficiency of the suggested fuzzy problem is further analyzed through a case study of Hazmat distribution in Iran.
RAIRO-OPERATIONS RESEARCH
(2022)
Review
Management
Seyed Sina Mohri, Mehrdad Mohammadi, Michel Gendreau, Amir Pirayesh, Ali Ghasemaghaei, Vahid Salehi
Summary: This paper provides a comprehensive review of hazardous material transportation from an Operational Research perspective, with a focus on hazmat routing, routing-scheduling, and network design problems. The paper reviews the assumptions, objectives, constraints, and solutions of the models, along with case studies. It also highlights the challenges and features of designing models for different transportation modes, and identifies research gaps and future directions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Computer Science, Interdisciplinary Applications
Feng Wang, Fanshu Liao, Yixuan Li, Xuesong Yan, Xu Chen
Summary: This paper proposes a new algorithm EL-DMOEA for solving the Dynamic Vehicle Routing Problem with Time Window, using ensemble learning method to improve algorithm performance. Multiple strategies are employed during training process to enhance population diversity and accelerate convergence, with experimental results showing promising routing plans can be effectively developed by the proposed algorithm.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Automation & Control Systems
Jianqiang Li, Junchuang Cai, Tao Sun, Qingling Zhu, Qiuzhen Lin
Summary: In this paper, a multitask-based evolutionary algorithm (MBEA) with knowledge transfer is proposed to solve the vehicle routing problem with simultaneous pickup-delivery and time windows (VRPSPDTW) in autonomous transportation. The algorithm tackles large-scale VRPSPDTW instances by utilizing multiple auxiliary tasks, facilitating the evolutionary search process. Experimental results demonstrate the effectiveness of the proposed algorithm in dealing with practical VRPSPDTW problems.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)
Article
Operations Research & Management Science
Sina Rastani, Bulent Catay
Summary: Range anxiety is a major barrier to the adoption of electric vehicles in logistics operations. The weight of the load carried plays a crucial role in the operational efficiency and routing decisions of electric vehicles.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Automation & Control Systems
Jiahui Duan, Zhenan He, Gary G. Yen
Summary: This article focuses on the robust multiobjective optimization approach for the vehicle routing problem with time windows under uncertainty. By designing a new form of disturbance on travel time and incorporating an advanced encoding and decoding scheme, the proposed algorithm is able to generate enough robust solutions and ensure the optimality of these solutions, as validated by experimental results.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Review
Green & Sustainable Science & Technology
Xiaobo Liu, Yen-Lin Chen, Lip Yee Por, Chin Soon Ku
Summary: Vehicle routing problems with time windows (VRPTW) have gained a lot of attention due to their important role in real-life logistics and transport. As a result of the complexity of real-life situations, most problems are multi-constrained and multi-objective, which increases their difficulty. This paper aims to contribute to the effective solution of VRPTW-related problems. Data extraction and analysis of the relevant literature within the last five years (2018-2022) are compared to answer the set research questions, and the results show the prevalence of approximate methods and hybrid approaches.
Article
Chemistry, Multidisciplinary
Mehmet Anil Akbay, Can Berk Kalayci, Christian Blum, Olcay Polat
Summary: This paper proposes a method to solve the two-echelon electric vehicle routing problem, aiming to reduce the negative impact in urban areas through multi-echelon distribution networks and environmentally friendly vehicles. A mixed-integer linear programming model is developed, and a variable neighborhood search metaheuristic is proposed to improve the solution quality.
APPLIED SCIENCES-BASEL
(2022)
Article
Engineering, Environmental
Jinkun Men, Guohua Chen, Lixing Zhou, Peizhu Chen
Summary: This study addresses the issue of considering multiple simultaneous HazMat shipments and proposes a multi-objective transportation network design model. The proposed algorithm is competitive in solving large-scale instances and effectively coordinates multiple HazMat transportation processes.
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
(2022)
Article
Engineering, Environmental
Min Huang, Guohua Chen, Peng Yang, Kun Hu, Lixing Zhou, Jinkun Men, Jie Zhao
Summary: Floods and hurricanes cause destructive damage to process equipment, especially vertical storage tanks, leading to severe technological accidents in chemical industrial parks. This study analyzes the buckling behavior of storage tanks under the coupling effect of floods and hurricanes, establishes a limit state equation for buckling failure, and investigates the factors affecting vulnerability through experimental and numerical simulations.
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
(2022)
Article
Engineering, Chemical
Guohua Chen, Xu Liang, Lixing Zhou, Jinkun Men
Summary: Chemical industrial parks (CIPs) are critical systems consisting of various units related to hazardous materials. Evacuation is a common strategy to mitigate casualties in chemical accidents, but current emergency evacuation plans lack quantifiable risk assessment and most studies ignore the temporal-spatial evolution of such accidents. This study proposes a multi-source and multi-sink evacuation model (MMEM) driven by dynamic risk assessment, which improves efficiency and safety by considering dynamic evolution characteristics and path conflicts caused by multiple evacuation crowds.
JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES
(2022)
Article
Engineering, Industrial
Jinkun Men, Guohua Chen, Yunfeng Yang, Genserik Reniers
Summary: This study proposes a systematic analytical framework to study the evolution mechanism of domino effects caused by natural hazards in chemical industrial parks. By developing an event-driven disaster chain evolution system and a system dynamic risk model, we can identify critical stages and intervals of the entire evolution process, providing support for the prevention and mitigation of such catastrophic chain events.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Engineering, Electrical & Electronic
Yaguang Kong, Xinghong Zhao, Guoqiang Jia, Jiangkun Hong, Fan Zhang
Summary: The electromagnetic field significantly affects the performance of wireless sensor networks (WSNs). The impact of electromagnetic field generated by power equipment on wireless sensor (WS) nodes can be characterized by two parameters: environmental electromagnetic interference factor (EEIF) and path loss index (PLI). EEIF is used to describe the sensing coverage probability in the sensor node probability model, while PLI is used in a node communication path loss model to evaluate the node communication quality in the electromagnetic interference environment. By combining a service cost model of wireless sensor networks in complex electromagnetic environments, the optimal deployment of wireless sensor networks in this environment can be achieved using the particle swarm optimization (PSO)-gray wolf optimizer (GWO) algorithm. Experimental results demonstrate the effectiveness of the proposed method in achieving optimal performance.
IEEE SENSORS JOURNAL
(2023)
Article
Engineering, Civil
Jinkun Men, Guohua Chen, Peizhu Chen, Lixing Zhou
Summary: This research addresses the problem of multi-crowd congestion-relieved evacuation in Gaussian Type-2 fuzzy environments. It proposes a path-based one destination network flow model with a multi-point diversion evacuation strategy to alleviate traffic congestion. Uncertainties in the evacuation process are handled using Gaussian Type-2 fuzzy variables and a critical value-based defuzzification technique. An efficient adaptive chaos particle swarm optimization algorithm is designed for model solving. The proposed methodology improves overall evacuation efficiency by coordinating multiple simultaneous evacuation processes.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Computer Science, Information Systems
Jinkun Men, Guohua Chen, Tao Zeng
Summary: The chemical process industry (CPI) is a high-risk industrial sector with frequent occurrence of multihazard coupling scenarios. However, there is a lack of systematic and comprehensive review on multihazard coupling studies in CPI. In this review, we analyze 184 relevant literature to systemize knowledge, identify research advances, and investigate future perspectives.
IEEE SYSTEMS JOURNAL
(2023)
Article
Computer Science, Information Systems
Jinkun Men, Guohua Chen, Tao Zeng
Summary: This review focuses on the multi-hazard coupling effects in the chemical process industry (CPI) and categorizes and investigates the existing research on this topic. The findings suggest that the related research is still in its early stages with great potential for future development.
IEEE SYSTEMS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Zhangping Chen, Na Huang, Jian Zhang, Fan Zhang, Yaguang Kong, Qiang Lu
Summary: In this paper, we investigate consensus seeking problems for second-order nonlinear multi-agent systems with unavailable velocity measurements. An event-triggered control strategy is proposed based on causally sampled position data only, which reduces the update frequencies of the controller and avoids continuous communications effectively. Sufficient conditions for achieving consensus are obtained by utilizing Lyapunov-Krasovskii stability theory and linear matrix inequality technique.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2023)
Article
Engineering, Environmental
Jinkun Men, Guohua Chen, Genserik Reniers, Xiaohui Rao, Tao Zeng
Summary: This study proposes a deep belief network-based label distribution learning system for estimating the seismic damage state probability distribution of liquid storage tanks. The methodology utilizes advanced deep learning framework, synthetic oversampling methods, and label enhancement techniques to achieve balanced estimation and robustness to label ambiguity.
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
(2023)
Article
Computer Science, Information Systems
Jiazhe Fan, Na Huang, Di Huang, Yaguang Kong, Zhangping Chen, Fan Zhang, Yao Zhang
Summary: This article proposes an improved path planning algorithm based on the dynamic window approach (DWA) to optimize real-time paths for agents in complex environments. It improves the weight of the evaluation function by designing adaptive laws, enhancing accuracy and adaptability. Additionally, strategies for escaping local minima and dealing with dynamic obstacles are presented, resulting in superior performance compared to the DWA algorithm in terms of running time, path length, and security.
IEEE SYSTEMS JOURNAL
(2023)
Article
Engineering, Chemical
Xiaohui Rao, Guohua Chen, Lixing Zhou, Chennan Luo, Jinkun Men, Saihua Jiang
Summary: This paper proposes an object-oriented modeling method that combines earthquake vulnerability assessment with 3D visualization technology to predict and characterize the damage state of critical infrastructure in oil transmission stations. A simulation system is designed and developed to enhance the 3D modeling efficiency of disaster scenes and improve public awareness of earthquake risks. The system can provide technical support for seismic mitigation planning and emergency management decision-making at oil transmission stations.
JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES
(2023)
Article
Computer Science, Artificial Intelligence
Jinkun Men, Chunmeng Zhao
Summary: With the increasing complexity and size of the modern chemical process industry, there is a growing demand for detecting potential faults as early as possible. However, the imbalanced fault patterns in continuous chemical process data streams hinder the generalization ability of fault diagnosis models. In this study, a novel adaptive imbalance modified online broad learning system (AIM-OBLS) is proposed to address this issue and has shown competitive performance on industrial datasets.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Qiming Xu, Guohua Chen, Shen Su, Jinkun Men, Geliang Li
Summary: This paper presents a novel approach that integrates explosive theory and data science to predict explosion overpressure and guide engineering design. A dimensionless mathematical formula was constructed based on explosive theory and used in data sets to consider various parameters. The predictive accuracy of this method was proven and showed better results compared to other models.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Fan Zhang, Leitao Qu, Wei Dong, Hongbo Zou, Qiang Guo, Yaguang Kong
Summary: Nonintrusive load monitoring is a technology that identifies users' energy consumption using data measured at a single point. This study proposes an event detection algorithm combining probability and expert heuristic models, which achieves high sensitivity and accuracy.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
