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Journal articles on the topic 'Genetic Algorithm; Vehicle Routing Problem; Optimal Path Planning'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Guo, Mei Ni. "Study on the Improvement of Genetic Algorithm by Using Vehicle Routing Problem." Applied Mechanics and Materials 365-366 (August 2013): 194–98. http://dx.doi.org/10.4028/www.scientific.net/amm.365-366.194.

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mprove the existing genetic algorithm, make the vehicle path planning problem solving can be higher quality and faster solution. The mathematic model for study of VRP with genetic algorithms was established. An improved genetic algorithm was proposed, which consist of a new method of initial population and partheno genetic algorithm revolution operation.Exploited Computer Aided Platform and Validated VRP by simulation software. Compared this improved genetic algorithm with the existing genetic algorithm and approximation algorithms through an example, convergence rate Much faster and the Optim

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Qi, Dingding, Yingjun Zhao, Zhengjun Wang, Wei Wang, Li Pi, and Longyue Li. "Joint Approach for Vehicle Routing Problems Based on Genetic Algorithm and Graph Convolutional Network." Mathematics 12, no. 19 (2024): 3144. http://dx.doi.org/10.3390/math12193144.

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The logistics demands of industries represented by e-commerce have experienced explosive growth in recent years. Vehicle path-planning plays a crucial role in optimization systems for logistics and distribution. A path-planning scheme suitable for an actual scenario is the key to reducing costs and improving service efficiency in logistics industries. In complex application scenarios, however, it is difficult for conventional heuristic algorithms to ensure the quality of solutions for vehicle routing problems. This study proposes a joint approach based on the genetic algorithm and graph convol

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Gao, Jia, Xiaojun Zheng, Feng Gao, Xiaoying Tong, and Qiaomei Han. "Heterogeneous Multitype Fleet Green Vehicle Path Planning of Automated Guided Vehicle with Time Windows in Flexible Manufacturing System." Machines 10, no. 3 (2022): 197. http://dx.doi.org/10.3390/machines10030197.

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In this study, we present and discuss a variant of the classical vehicle routing problem (VRP), namely the heterogeneous multitype fleet green automated guided vehicle (AGV) routing problem with time windows (HFGVRPTW) applied in the workshops of flexible manufacturing systems (FMS). Specifically, based on the analysis of AGV body structure and motion state, transport distance and energy consumption are selected as two optimization objectives. According to the characteristics and application context of the problem, this paper designs a hybrid genetic algorithm with large neighborhood search (G

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Chen, Chien-Ming, Shi Lv, Jirsen Ning, and Jimmy Ming-Tai Wu. "A Genetic Algorithm for the Waitable Time-Varying Multi-Depot Green Vehicle Routing Problem." Symmetry 15, no. 1 (2023): 124. http://dx.doi.org/10.3390/sym15010124.

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In an era where people in the world are concerned about environmental issues, companies must reduce distribution costs while minimizing the pollution generated during the distribution process. For today’s multi-depot problem, a mixed-integer programming model is proposed in this paper to minimize all costs incurred in the entire transportation process, considering the impact of time-varying speed, loading, and waiting time on costs. Time is directional; hence, the problems considered in this study are modeled based on asymmetry, making the problem-solving more complex. This paper proposes a ge

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Mrinmoyee, Chattoraj, and Udaya Rani.V Dr. "A SOFT COMPUTING APPROACH FOR SMOOTH TRAFFIC FLOW ON ROAD NETWORK." International Journal of Research - Granthaalayah 5, no. 4 (2017): 311–19. https://doi.org/10.5281/zenodo.573002.

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Route planning has an important role in navigation systems. In order to select an optimized route the traveller has to take various factors into consideration. Traffic congestion is an important factor which needs to be considered while route planning. As the numbers of vehicles are increasing on the road the traffic congestion is also increasing in an exponential manner. In a congested area the best approach to search for a route is to select an alternative path so that we can reach our destination and indirectly save some time. In the recent years route planning system has become an importan

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Yang, Lin, Qinghua Chen, Junjie Mu, Tangying Liu, Xiaoxiao Li, and Shuxiang Cai. "Research on Capacitated Multi-Ship Replenishment Path Planning Problem Based on the Synergistic Hybrid Optimization Algorithm." Biomimetics 10, no. 5 (2025): 285. https://doi.org/10.3390/biomimetics10050285.

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Ship replenishment path planning is a critical problem in the field of maritime logistics. This study proposes a novel synergistic hybrid optimization algorithm (SHOA) that effectively integrates ant colony optimization (ACO), the Clarke–Wright algorithm (CW), and the genetic algorithm (GA) to solve the capacitated multi-ship replenishment path planning problem (CMSRPPP). The proposed methodology employs a three-stage optimization framework: (1) initial path generation via parallel execution of the CW and ACO; (2) population initialization for the GA by strategically combining optimal solution

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Zhang, Qinglong, Naifu Deng, Yanwen Zhu, and Zhenping Huang. "Multidepot Two-Echelon Vehicle Routing Problem for Earthwork Allocation Optimization." Mathematical Problems in Engineering 2022 (January 29, 2022): 1–14. http://dx.doi.org/10.1155/2022/8373138.

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Prior to the construction of most engineering projects, earthwork is a complex and time-consuming task, requiring iterative operations in civil engineering. The effectiveness of earthworks determines the cost of many AEC (architecture, engineering, and construction) projects (e.g., road, embankment, railway, and slope engineering). As a result, creating effective earthwork planning is critical. The earthwork allocation problem is simplified in this study to the vehicle route problem (VRP), which is often studied in the field of transportation and logistics. An optimization model for the earthw

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Chen, Lei, Haiyan Ma, Yi Wang, and Feng Li. "Vehicle Routing Problem for the Simultaneous Pickup and Delivery of Lithium Batteries of Small Power Vehicles under Charging and Swapping Mode." Sustainability 14, no. 16 (2022): 9883. http://dx.doi.org/10.3390/su14169883.

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Due to the national policy of encouraging the development of power exchange modes, the reasonable planning of vehicle distribution paths to meet the demand of lithium battery power exchange points has become a topic of considerable research interest. In this study, we propose the “centralized charging + unified distribution” power exchange mode for optimizing the charging and transporting of lithium batteries. Considering lithium batteries are dangerous goods, the vehicle path problem of simultaneous pickup and delivery of lithium batteries with vehicle load and soft time window constraints is

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Albalawneh, Da’ad Ahmad, and Mohamad Afendee Mohamed. "Evaluation of Using Genetic Algorithm and ArcGIS for Determining the Optimal-Time Path in the Optimization of Vehicle Routing Applications." Mathematical Problems in Engineering 2022 (September 27, 2022): 1–20. http://dx.doi.org/10.1155/2022/7769951.

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Transportation is regarded as one of the most important issues currently being researched; this issue needs the search for approaches or processes that might lessen many contemporary traffic concerns. Congestion, pollution, and accidents have escalated lately, negatively impacting urban environments, economic development, and citizens’ lifestyles. The rise of illnesses and epidemics throughout the world, such as COVID-19, has created an urgent need to find the best way to save people’s lives. The vehicle routing problem (VRP) is a well-known moniker for improving transportation systems and is

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Saputra, Arie, and Desi Fadhilah. "Optimasi Jalur Distribusi Menggunakan Pendekatan Algoritma Genetika." Jurnal Optimalisasi 10, no. 2 (2024): 244. https://doi.org/10.35308/jopt.v10i2.10601.

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Management and planning of transportation distribution channels are important in increasing the company's operational efficiency. Optimal distribution arrangements can reduce transportation costs and time, as well as increase product competitiveness in the market. One method used to determine the best distribution route is the Traveling Salesman Problem (TSP), which helps companies achieve maximum efficiency. This research was carried out at the AMDK CV company. Tirta Naga Lestari (TNL) as a case study to analyze product distribution to 11 locations in Aceh. Unplanned product distribution caus

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Kouretas, Konstantinos, and Konstantinos Kepaptsoglou. "Planning Integrated Unmanned Aerial Vehicle and Conventional Vehicle Delivery Operations under Restricted Airspace: A Mixed Nested Genetic Algorithm and Geographic Information System-Assisted Optimization Approach." Vehicles 5, no. 3 (2023): 1060–86. http://dx.doi.org/10.3390/vehicles5030058.

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Using Unmanned Aerial Vehicles (UAVs), commonly referred to as “drones”, as a supplementary mode for last-mile deliveries has been a research focus for some years now. Motivation lies in the reduced dependency on Conventional Vehicles (CVs) and fossil fuels and in serving remote areas and underprivileged populations. We are building a flexible, modular framework for integrated CV-UAV parcel delivery operations planning that is responsive to infrastructure and demand and offers an open and practical tool for future adaptations. The entire model and solution methodology are practical tools for d

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Huang, Min, and Ping Ding. "An Improved Ant Colony Algorithm and Its Application in Vehicle Routing Problem." Mathematical Problems in Engineering 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/785383.

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Optimal path planning is an important issue in vehicle routing problem. This paper proposes a new vehicle routing path planning method which adds path weight matrix and save matrix. The method uses a new transition probability function adding the angle factor function and visibility function, while setting penalty function in a new pheromone updating model to improve the accuracy of the route searching. Finally, after each cycle, we use 3-opt method to update the optimal solution to optimize the path length. The results of comparison also confirm that this method is better than the traditional

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Ding, Xiaoyin, Jun Zhou, Jian Cai, et al. "Based on Particle Group Algorithm of Route Planning for Transportable Charging Station." Journal of Physics: Conference Series 2025, no. 1 (2021): 012044. http://dx.doi.org/10.1088/1742-6596/2025/1/012044.

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Abstract Aiming at the problem of path planning for transportable charging stations, a site selection model and path planning model for dedicated routes for transportable charging stations are proposed. The path planning problem model includes the vehicle path problem and the dynamic path problem, and the path planning model is emphatically studied. Considering the network optimization model of chargers and transportable charging station paths, by establishing a path planning model, setting parameters and models, using particle swarm algorithm to calculate the path planning model of chargers a

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WU, S., and C. CHEN. "MULTI-OBJECTIVE DISTRIBUTION ROUTING OPTIMIZATION WITH TIME WINDOW BASED ON IMPROVED GENETIC ALGORITHM." Latin American Applied Research - An international journal 48, no. 3 (2018): 151–56. http://dx.doi.org/10.52292/j.laar.2018.218.

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In order to solve the shortcomings of the traditional genetic algorithm in solving the problem of logistics distribution path, a modified genetic algorithm is proposed to solve the Vehicle Routing Problem with Time Windows (VRPTW) under the condition of vehicle load and time window. In the crossover process, the best genes can be preserved to reduce the inferior individuals resulting from the crossover, thus improving the convergence speed of the algorithm. A mutation operation is designed to ensure the population diversity of the algorithm, reduce the generation of infeasible solutions, and i

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WANG, Mengqin, and Qiyue XIE. "Logistics Pure Electric Vehicle Routing Based on GA-PSO Algorithm." Mechanics 29, no. 3 (2023): 235–42. http://dx.doi.org/10.5755/j02.mech.31954.

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Abstract:Based on current energy storage technologies such as batteries and fuel cells, the inherent battery capacity of electric vehicles puts constraints on their driving range and requires charging in the process of completing driving tasks. In this paper, with the current practical application in logistics industry as the background, from electric vehicle charging scheduling and path planning, a hybrid algorithm combining genetic-particle swarm algorithm is proposed to plan the best driving route for a group of electric logistics vehicles with vehicle load, vehicle battery life, charging f

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Li, H. H., H. R. Fu, and W. H. Li. "Skin lesion segmentation method for dermoscopic images with convolutional neural networks and semantic segmentation." Computer Optics 45, no. 1 (2021): 154–60. http://dx.doi.org/10.18287/2412-6179-co-732.

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With the development of economy, the distribution problem of logistics becomes more and more complex. Based on the traffic network data, this study analyzed the vehicle routing problem (VRP), designed a dynamic vehicle routing problem with time window (DVRPTW) model, and solved it with genetic algorithm (GA). In order to improve the performance of the algorithm, the genetic operation was improved, and the output solution was further optimized by hill climbing algorithm. The analysis of example showed that the improved GA algorithm had better performance in path optimization planning, the total

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Zhou, Jianxu. "Research on multi-path optimization problem based on particle swarm optimization algorithm." Theoretical and Natural Science 43, no. 1 (2024): 156–61. http://dx.doi.org/10.54254/2753-8818/43/20240857.

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The problem of finding the optimal path within a certain range exists in various scenarios in our lives, such as the traveling salesman problem, robot automatic path selection problem, vehicle and pedestrian navigation, game path navigation, communication routing, logistics and transportation planning problems, etc. , through the optimization of path problems, we can help people improve resource utilization, improve work efficiency, reduce production costs, or complete the goal of a specific scenario, etc. Therefore, solving the path optimization problem is a very important task in our reality

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Ma, Fangfang. "Multimedia Urban Road Path Optimization Based on Genetic Algorithm." Computational Intelligence and Neuroscience 2022 (April 30, 2022): 1–8. http://dx.doi.org/10.1155/2022/7898871.

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In order to study multimedia urban road path optimization based on genetic algorithm, a dynamic path optimization based on genetic algorithm is proposed. Firstly, for the current situation of traffic congestion, time constraints are strictly considered based on the traditional hard time window logistics distribution vehicle scheduling problem model. Then, the mathematical model is established, and the optimal solution is solved by the combination of decomposition coordination algorithm and genetic algorithm. We divide multiple customers into different customer groups and determine the service

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Kareem, Abbas Abdulrazzaq, Mohamed Jasim Mohamed, and Bashra Kadhim Oleiwi. "Unmanned aerial vehicle path planning in a 3D environment using a hybrid algorithm." Bulletin of Electrical Engineering and Informatics 13, no. 2 (2024): 905–15. http://dx.doi.org/10.11591/eei.v13i2.6020.

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The optimal unmanned aerial vehicle (UAV) path planning using bio-inspired algorithms requires high computation and low convergence in a complex 3D environment. To solve this problem, a hybrid A*-FPA algorithm was proposed that combines the A* algorithm with a flower pollination algorithm (FPA). The main idea of this algorithm is to balance the high speed of the A* exploration ability with the FPA exploitation ability to find an optimal 3D UAV path. At first, the algorithm starts by finding the locally optimal path based on a grid map, and the result is a set of path nodes. The algorithm will

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Zeng, Xinzhu, and Yiding Wang. "Multi-objective Logistics Distribution Path Optimization Based on Annealing Evolution Algorithm." Journal of Physics: Conference Series 2555, no. 1 (2023): 012014. http://dx.doi.org/10.1088/1742-6596/2555/1/012014.

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Abstract Logistics distribution is a collection of interrelated organizations and facilities. There is a waste of cost and time in many links. Therefore, it is particularly important to use information technology to improve distribution efficiency. Under the constraints of delivery vehicle cost and time, this paper proposes an improved genetic simulated annealing algorithm (SAGA), which combines the global search ability of the genetic algorithm (GA) and the simulated annealing algorithm (SA) with strong local search ability to solve the vehicle routing problem with time windows (VRPTW). The p

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Han, Xue. "Path Planning Algorithm for the Multiple Depot Vehicle Routing Problem Based on Parallel Clustering." Scientific Programming 2023 (April 25, 2023): 1–12. http://dx.doi.org/10.1155/2023/7588595.

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It is necessary to study the problem of vehicle routing in multidistribution centers to improve the speed, time, and cost thereof. It is preferable to use as few vehicles as possible to complete the delivery of goods and minimize the total mileage. With the development of artificial intelligence technology, machine learning is usually used to solve the problem of k shortest paths in multiple distribution centers. User needs are constantly changing; the iterative convergence speed of traditional machine learning methods is low and cannot meet the requirements of path planning in a big-data envi

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Parsons, Tyler, Farhad Baghyari, Jaho Seo, Byeongjin Kim, Mingeuk Kim, and Hanmin Lee. "Surveillance Unmanned Ground Vehicle Path Planning with Path Smoothing and Vehicle Breakdown Recovery." Applied Sciences 14, no. 16 (2024): 7266. http://dx.doi.org/10.3390/app14167266.

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As unmanned ground vehicles (UGV) continue to be adapted to new applications, an emerging area lacks proper guidance for global route optimization methodology. This area is surveillance. In autonomous surveillance applications, a UGV is equipped with a sensor that receives data within a specific range from the vehicle while it traverses the environment. In this paper, the ant colony optimization (ACO) algorithm was adapted to the UGV surveillance problem to solve for optimal paths within sub-areas. To do so, the problem was modeled as the covering salesman problem (CSP). This is one of the fir

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Chai, Huo, Ruichun He, Changxi Ma, Cunjie Dai, and Kun Zhou. "Path Planning and Vehicle Scheduling Optimization for Logistic Distribution of Hazardous Materials in Full Container Load." Discrete Dynamics in Nature and Society 2017 (2017): 1–13. http://dx.doi.org/10.1155/2017/9685125.

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Mathematical models for path planning and vehicle scheduling for logistic distribution of hazardous materials in full container load (FCL) are established, with their problem-solving methods proposed. First, a two-stage multiobjective optimization algorithm is designed for path planning. In the first stage, pulse algorithm is used to obtain the Pareto paths from the distribution center to each destination. In the second stage, a multiobjective optimization method based on Nondominated Sorting Genetic Algorithm II (NSGA-II) is designed to obtain candidate transport paths. Second, with analysis

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Elgarej, Mouhcine, Mansouri Khalifa, and Mohamed Youssfi. "Optimized Path Planning for Electric Vehicle Routing and Charging Station Navigation Systems." International Journal of Applied Metaheuristic Computing 11, no. 3 (2020): 58–78. http://dx.doi.org/10.4018/ijamc.2020070103.

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With the increase in the number of electric vehicles (EV) on the street in the last years, the drivers of EVs are suffering from the problem of guiding themselves toward the nearest charging stations for recharging their batteries or finding the shortest routes toward their destinations. Although, the electric vehicle planning problem (EPP) is designed to achieve several transactions such as battery energy restrictions and the challenge of finding the nearest charging stations to the position of the electric vehicle. In this work, a new distributed system for electric vehicle routing is based

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Xin, Junfeng, Jiabao Zhong, Fengru Yang, Ying Cui, and Jinlu Sheng. "An Improved Genetic Algorithm for Path-Planning of Unmanned Surface Vehicle." Sensors 19, no. 11 (2019): 2640. http://dx.doi.org/10.3390/s19112640.

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The genetic algorithm (GA) is an effective method to solve the path-planning problem and help realize the autonomous navigation for and control of unmanned surface vehicles. In order to overcome the inherent shortcomings of conventional GA such as population premature and slow convergence speed, this paper proposes the strategy of increasing the number of offsprings by using the multi-domain inversion. Meanwhile, a second fitness evaluation was conducted to eliminate undesirable offsprings and reserve the most advantageous individuals. The improvement could help enhance the capability of local

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Li, Jiaqi, Yun Wang, and Ke-Lin Du. "Distribution Path Optimization by an Improved Genetic Algorithm Combined with a Divide-and-Conquer Strategy." Technologies 10, no. 4 (2022): 81. http://dx.doi.org/10.3390/technologies10040081.

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The multivehicle routing problem (MVRP) is a variation of the classical vehicle routing problem (VRP). The MVRP is to find a set of routes by multiple vehicles that serve multiple customers at a minimal total cost while the travelling-time delay due to traffic congestion is tolerated. It is an NP problem and is conventionally solved by metaheuristics such as evolutionary algorithms. For the MVRP in a distribution network, we propose an optimal distribution path optimization method that is composed of a distribution sequence search stage and a distribution path search stage that exploits a divi

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Liu, Zhiqiang, Weidong Wang, Junyi He, et al. "A New Hybrid Algorithm for Vehicle Routing Optimization." Sustainability 15, no. 14 (2023): 10982. http://dx.doi.org/10.3390/su151410982.

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To solve the vehicle routing problem with simultaneous pickup–delivery and time windows (VRPSDPTW), a sine cosine and firefly perturbed sparrow search algorithm (SFSSA) is presented. Based on the standard sparrow search algorithm, the initial population uses tent chaotic mapping to change the population diversity; then, the discoverer location is updated using the sine cosine fluctuation range of the random weight factor, and finally the global population location is updated using the firefly perturbation strategy. In this study, SFSSA was compared with a genetic algorithm (GA), parallel simul

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Shabaev, Anton, Anton Sokolov, Alexander Urban, and Dmitry Pyatin. "An approach to the optimal timber transport scheduling." E3S Web of Conferences 164 (2020): 03019. http://dx.doi.org/10.1051/e3sconf/202016403019.

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An approach to the optimal timber transport scheduling is described in the paper. A description of this problem is given, a multi-criteria mathematical model is created. It is noted that the problem belongs to the class of General vehicle routing problems (GVRP) associated with the job-shop scheduling. A hybrid algorithm for solving this problem based on the decomposition method using the simplex method and the genetic algorithm is developed. Testing of the proposed approach using real data from wood harvesting enterprises showed its effectiveness. The algorithm was implemented in “Opti-Wood”

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Yuan, Yunmei, Hongyu Li, and Lili Ji. "Application of Deep Reinforcement Learning Algorithm in Uncertain Logistics Transportation Scheduling." Computational Intelligence and Neuroscience 2021 (September 25, 2021): 1–9. http://dx.doi.org/10.1155/2021/5672227.

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Nowadays, finding the optimal route for vehicles through online vehicle path planning is one of the main problems that the logistics industry needs to solve. Due to the uncertainty of the transportation system, especially the last-mile delivery problem of small packages in uncertain logistics transportation, the calculation of logistics vehicle routing planning becomes more complex than before. Most of the existing solutions are less applied to new technologies such as machine learning, and most of them use a heuristic algorithm. This kind of solution not only needs to set a lot of constraints

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Zhou, Zhongxin, Minghu Ha, Hao Hu, and Hongguang Ma. "Half Open Multi-Depot Heterogeneous Vehicle Routing Problem for Hazardous Materials Transportation." Sustainability 13, no. 3 (2021): 1262. http://dx.doi.org/10.3390/su13031262.

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How to reduce the accidents of hazardous materials has become an important and urgent research topic in the safety management of hazardous materials. In this study, we focus on the half open multi-depot heterogeneous vehicle routing problem for hazardous materials transportation. The goal is to determine the vehicle allocation and the optimal route with minimum risk and cost for hazardous materials transportation. A novel transportation risk model is presented considering the variation of vehicle loading, vehicle types, and hazardous materials category. In order to balance the transportation r

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Wang, D. L., A. Ding, G. L. Chen, and L. Zhang. "A combined genetic algorithm and A* search algorithm for the electric vehicle routing problem with time windows." Advances in Production Engineering & Management 18, no. 4 (2023): 403–16. http://dx.doi.org/10.14743/apem2023.4.481.

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With growing environmental concerns, the focus on greenhouse gases (GHG) emissions in transportation has increased, and the combination of smart microgrids and electric vehicles (EVs) brings a new opportunity to solve this problem. Electric vehicle routing problem with time windows (EVRPTW) is an extension of the vehicle routing problem (VRP) problem, which can reach the combination of smart microgrids and EVs precisely by scheduling the EVs. However, the current genetic algorithm (GA) for solving this problem can easily fall into the dilemma of local optimization and slow iteration speed. In

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Peng, Ya Li, Jia Yao Liu, and Hong Yin. "Research on Vehicle Path Planning Based on the BDD in the Uncertain Environment." Applied Mechanics and Materials 373-375 (August 2013): 1144–49. http://dx.doi.org/10.4028/www.scientific.net/amm.373-375.1144.

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Aimed at the high dynamics and uncertainty of road traffic, we propose a method combine BDD (binary decision diagram)-Based heuristic algorithm which used to do the initial path planning with BDD-Based incremental to solve the route replanning problem. In order to get the optimal path set, BDD-Based heuristic Search is firstly used for global planning. BDD is a compact data structure, the BDD-Based heuristic Search use this characteristic to represent state space and compress the search space through heuristic information at the same time; when the road network information changes, incremental

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Wei, Haitao, Shusheng Zhang, and Xiaohui He. "Shortest Path Algorithm in Dynamic Restricted Area Based on Unidirectional Road Network Model." Sensors 21, no. 1 (2020): 203. http://dx.doi.org/10.3390/s21010203.

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Accurate and fast path calculation is essential for applications such as vehicle navigation systems and transportation network routing. Although many shortest path algorithms for restricted search areas have been developed in the past ten years to speed up the efficiency of path query, the performance including the practicability still needs to be improved. To settle this problem, this paper proposes a new method of calculating statistical parameters based on a unidirectional road network model that is more in line with the real world and a path planning algorithm for dynamically restricted se

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Cong, Ying, and Kai Zhu. "Research on Vehicle Path Planning Method with Time Windows in Uncertain Environments." World Electric Vehicle Journal 15, no. 12 (2024): 566. https://doi.org/10.3390/wevj15120566.

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With the growing complexity of logistics and the demand for sustainability, the vehicle routing problem (VRP) has become a key research area. Classical VRPs now incorporate practical challenges such as time window constraints and carbon emissions. In uncertain environments, where many factors are stochastic or fuzzy, optimization models based on uncertainty theory have gained increasing attention. A single-objective optimization model is proposed in this paper to minimize the total cost of VRP in uncertain environments, including fixed costs, transportation costs, and carbon emission costs. Pr

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Fan, Linsheng. "Routing optimization method of waste transportation vehicle using biological evolutionary algorithm under the perspective of low carbon and environmental protection." Environmental Engineering Research 28, no. 1 (2022): 210458–0. http://dx.doi.org/10.4491/eer.2021.458.

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Reasonably and effectively formulating the best route for urban waste transportation vehicle is particularly important for realizing low carbon and environmental protection of Green China construction concept. However, the current path planning method has shortcomings such as local optimization. In order to solve this problem, this paper aims at low carbon and environmental protection construction needs and proposes a routing optimization method of waste transportation vehicles based on improved ant colony algorithm. Firstly, the mathematical model of Vehicle Routing Problem (VRP) is construct

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Du, Lijing, Xiaohuan Li, Yuan Gan, and Kaijun Leng. "Optimal Model and Algorithm of Medical Materials Delivery Drone Routing Problem under Major Public Health Emergencies." Sustainability 14, no. 8 (2022): 4651. http://dx.doi.org/10.3390/su14084651.

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To reduce distribution risk and improve the efficiency of medical materials delivery under major public health emergencies, this paper introduces a drone routing problem with time windows. A mixed-integer programming model is formulated considering contactless delivery, total travel time, and customer service time windows. Utilizing Dantzig–Wolfe decomposition, the proposed optimization model is converted into a path-based master problem and a pricing subproblem based on an elementary shortest path problem with resource constraints. We embed the pulse algorithm into a column generation framewo

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Song, Rui, Wanen Qin, Wen Shi, and Xingjian Xue. "Optimizing Freight Vehicle Routing in Dynamic Time-Varying Networks with Carbon Dioxide Emission Trajectory Analysis." Sustainability 15, no. 21 (2023): 15504. http://dx.doi.org/10.3390/su152115504.

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In this study, we formulate a freight vehicle path-planning model in the context of dynamic time-varying networks that aims to capture the spatial and temporal distribution characteristics inherent in the carbon dioxide emission trajectories of freight vehicles. Central to this model is the minimization of total carbon dioxide emissions from vehicle distribution, based on the comprehensive modal emission model (CMEM). Our model also employs the freight vehicle travel time discretization technique and the dynamic time-varying multi-path selection strategy. We then design an improved genetic alg

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Zheng, Xiaojun, Feng Gao, and Xiaoying Tong. "Research on Green Vehicle Path Planning of AGVs with Simultaneous Pickup and Delivery in Intelligent Workshop." Symmetry 15, no. 8 (2023): 1505. http://dx.doi.org/10.3390/sym15081505.

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In this study, we present and discuss a variant of the classic vehicle routing problem (VRP), the green automated guided vehicle (AGV) routing problem, which involves simultaneous pickup and delivery with time windows (GVRPSPDTW) in an intelligent workshop. The research object is AGV energy consumption. First, we conduct a comprehensive analysis of the mechanical forces present during AGV transportation and evaluate the overall operational efficiency of the workshop. Then, we construct a green vehicle path planning model to minimize the energy consumption during AGV transportation and the stan

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Tang, Yongwei, Jun Zhou, Huijuan Hao, Fengqi Hao, and Haigang Xu. "Path Planning and Trajectory Tracking for Automatic Guided Vehicles." Computational Intelligence and Neuroscience 2022 (July 14, 2022): 1–11. http://dx.doi.org/10.1155/2022/8981778.

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Automated guided vehicle technology has become a hot area of scientific research due to its increasing use in manufacturing and logistics. Its main features are programming and control, remote computer eye tracking, command receiving and execution, autonomous route planning, and autonomous driving execution of tasks, with the advantages of high intelligence and flexibility. In this work, a simple vehicle model is used to study the route planning and tracking control of automatic guided vehicles. This paper uses wireless communication to find the optimal route planning problem. Using geometric

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Wang, Biao. "Optimization of Multi-Vehicle Routing Problem with Time Windows and Simultaneous Pickup and Delivery." Journal of Electronic Research and Application 9, no. 3 (2025): 350–58. https://doi.org/10.26689/jera.v9i3.10815.

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This paper addresses the Multi-Vehicle Routing Problem with Time Windows and Simultaneous Pickup and Delivery (MVRPTWSPD), aiming to optimize logistics distribution routes and minimize total costs. A vehicle routing optimization model is developed based on the operational requirements of the KS Logistics Center, focusing on minimizing vehicle dispatch, loading and unloading, operating, and time window penalty costs. The model incorporates constraints such as vehicle capacity, time windows, and travel distance, and is solved using a genetic algorithm to ensure optimal route planning. Through MA

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Lin, Chaoxiong, and Xuecong Zhang. "Application of UAV path planning based on parameter optimization GA-PSO fusion algorithm." Journal of Physics: Conference Series 2258, no. 1 (2022): 012018. http://dx.doi.org/10.1088/1742-6596/2258/1/012018.

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Abstract Aiming at the complexity of the unmanned aerial vehicle (UAV) path planning problem and the great influence of genetic algorithm parameters on the stability of the results, a fusion algorithm based on parameter optimization is proposed in this paper. In the iterative process, the GA-PSO fusion algorithm uses particle swarm optimization algorithm to search the optimal value of crossover rate and mutation rate in genetic algorithm, which makes the algorithm convergence speed is fast and search ability is strong. In addition, the core part of the algorithm fusion framework is realized by

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Deng, Naifu, Xuyang Li, and Yanmin Su. "Optimization of Earthwork Allocation Path as Vehicle Route Problem Based on Genetic Algorithm." E3S Web of Conferences 165 (2020): 04057. http://dx.doi.org/10.1051/e3sconf/202016504057.

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In civil engineering, earthwork, prior to the construction of most engineering projects, is a lengthy and time-consuming work involving iterative processes. The cost of many AEC (Architecture, Engineering and Construction) projects is highly dependent on the efficiency of earthworks (e.g. road, embankment, railway and slope engineering). Therefore, designing proper earthwork planning is of importance. This paper simplifies the earthwork allocation problem to Vehicle Route Problem (VRP) which is commonly discussed in the field of transportation and logistics. An optimization model for the earth

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Asih, Hayati Mukti, Raden Achmad Chairdino Leuveano, Dhimas Arief Dharmawan, and Ardiansyah Ardiansyah. "A genetic algorithm approach to green vehicle routing: Optimizing vehicle allocation and route planning for perishable products." International Journal of Advances in Intelligent Informatics 11, no. 2 (2025): 175. https://doi.org/10.26555/ijain.v11i2.1784.

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This paper introduces a novel approach to the Green Vehicle Routing Problem (GVRP) by integrating multiple trips, heterogeneous vehicles, and time windows, specifically applied to the distribution of bakery products. The primary objective of the proposed model is to optimize route planning and vehicle allocation, aiming to minimize transportation costs and carbon emissions while maximizing product quality upon delivery to retailers. Utilizing a Genetic Algorithm (GA), the model demonstrates its effectiveness in achieving near-optimal solutions that balance economic, environmental, and quality-

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He, Dan. "Intelligent Selection Algorithm of Optimal Logistics Distribution Path Based on Supply Chain Technology." Computational Intelligence and Neuroscience 2022 (April 14, 2022): 1–8. http://dx.doi.org/10.1155/2022/9955726.

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How to realize the intelligence of logistics distribution is a hot research topic at present. How to reasonably allocate vehicles, optimize driving routes and travel time, deliver goods to customers on time at the lowest cost, and realize efficient and low-cost operation of the logistics distribution system has always been a problem in academia and industry for many years. Logistics enterprises face problems such as low efficiency of logistics operation, lack of scientific rationality of logistics resource planning, and lack of overall optimization of logistics management operation mode. These

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Hsiao, Yu-Hsiang, Mu-Chen Chen, Kuan-Yu Lu, and Cheng-Lin Chin. "Last-mile distribution planning for fruit-and-vegetable cold chains." International Journal of Logistics Management 29, no. 3 (2018): 862–86. http://dx.doi.org/10.1108/ijlm-01-2017-0002.

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Purpose The purpose of this paper is to formulate and solve a last-mile distribution plan problem with concern for the quality of fruits and vegetables in cold chains. Design/methodology/approach The vehicle routing problem with time windows (VRPTW) is extended based on the characteristics of fruit-and-vegetable cold chains. The properties of multiple perishable foods, continuing decline in quality, various requirements for quality levels and optimal temperature settings during vehicle transportation are considered in the VRPTW. The product quality level is defined by the estimation of residua

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Chen, Yang, Jianda Han, and Xingang Zhao. "Three-dimensional path planning for unmanned aerial vehicle based on linear programming." Robotica 30, no. 5 (2011): 773–81. http://dx.doi.org/10.1017/s0263574711000993.

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SUMMARYIn this paper, an approach based on linear programming (LP) is proposed for path planning in three-dimensional space, in which an aerial vehicle is requested to pursue a target while avoiding static or dynamic obstacles. This problem is very meaningful for many aerial robots, such as unmanned aerial vehicles. First, the tasks of target-pursuit and obstacle-avoidance are modelled with linear constraints in relative coordination according to LP formulation. Then, two weighted cost functions, representing the optimal velocity resolution, are integrated into the final objective function. Th

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Tan, Aiping, Chang Wang, Yan Wang, and Chenglong Dong. "Electric Vehicle Charging Route Planning for Shortest Travel Time Based on Improved Ant Colony Optimization." Sensors 25, no. 1 (2024): 176. https://doi.org/10.3390/s25010176.

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Electric vehicles (EVs) are gaining significant attention as an environmentally friendly transportation solution. However, limitations in battery technology continue to restrict EV range and charging speed, resulting in range anxiety, which hampers widespread adoption. While there has been increasing research on EV route optimization, personalized path planning that caters to individual user needs remains underexplored. To bridge this gap, we propose the electric vehicle charging route planning based on user requirements (EVCRP-UR) problem, which aims to integrate user preferences and multiple

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Li, Jin, Feng Wang, and Yu He. "Electric Vehicle Routing Problem with Battery Swapping Considering Energy Consumption and Carbon Emissions." Sustainability 12, no. 24 (2020): 10537. http://dx.doi.org/10.3390/su122410537.

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In this paper, we study an electric vehicle routing problem while considering the constraints on battery life and battery swapping stations. We first introduce a comprehensive model consisting of speed, load and distance to measure the energy consumption and carbon emissions of electric vehicles. Second, we propose a mixed integer programming model to minimize the total costs related to electric vehicle energy consumption and travel time. To solve this model efficiently, we develop an adaptive genetic algorithm based on hill climbing optimization and neighborhood search. The crossover and muta

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Vidal, Thibaut, Rafael Martinelli, Tuan Anh Pham, and Minh Hoàng Hà. "Arc Routing with Time-Dependent Travel Times and Paths." Transportation Science 55, no. 3 (2021): 706–24. http://dx.doi.org/10.1287/trsc.2020.1035.

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Vehicle routing algorithms usually reformulate the road network into a complete graph in which each arc represents the shortest path between two locations. Studies on time-dependent routing followed this model and therefore defined the speed functions on the complete graph. We argue that this model is often inadequate, in particular for arc routing problems involving services on edges of a road network. To fill this gap, we formally define the time-dependent capacitated arc routing problem (TDCARP), with travel and service speed functions given directly at the network level. Under these assump

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Sun, Guofeng, Zhiqiang Tian, Renhua Liu, Yun Jing, and Yawen Ma. "Research on Coordination and Optimization of Order Allocation and Delivery Route Planning in Take-Out System." Mathematical Problems in Engineering 2020 (July 23, 2020): 1–16. http://dx.doi.org/10.1155/2020/7248492.

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This paper studies the take-out route delivery problem (TRDP) with order allocation and unilateral soft time window constraints. The TRDP considers the order allocation and delivery route optimization in the delivery service process. The TRDP is a challenging version of vehicle routing problem. In order to solve this problem, this paper aims to minimize the total cost of delivery, builds an optimization model of this problem by using cumulative time, and adds time dimension in order allocation and path optimization dimensions. It can not only track the real-time location of delivery personnel

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