A solution for simultaneous adaptive ant colony algorithm to memory demand vehicle routing problem with pickups

Wang, Rui; Zheng, Danyang; Zhang, Hongdou; Mao, Jianlin; Guo, Ning

doi:10.1109/ccdc.2016.7531345

Cited by 3 publications

(2 citation statements)

References 3 publications

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“…The first iteration AMP is run so that it can cover the drawback of AAC falling into local minimum and on the result of AMP, i.e., a second iteration of AAC is run. By doing this, we have seen that the path length is minimized for vehicle path planning used in logistics [81].…”

Section: Ant Colony Algorithmmentioning

confidence: 99%

A Survey of Path Planning Algorithms for Mobile Robots

et al. 2021

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Path planning algorithms are used by mobile robots, unmanned aerial vehicles, and autonomous cars in order to identify safe, efficient, collision-free, and least-cost travel paths from an origin to a destination. Choosing an appropriate path planning algorithm helps to ensure safe and effective point-to-point navigation, and the optimal algorithm depends on the robot geometry as well as the computing constraints, including static/holonomic and dynamic/non-holonomically-constrained systems, and requires a comprehensive understanding of contemporary solutions. The goal of this paper is to help novice practitioners gain an awareness of the classes of path planning algorithms used today and to understand their potential use cases—particularly within automated or unmanned systems. To that end, we provide broad, rather than deep, coverage of key and foundational algorithms, with popular algorithms and variants considered in the context of different robotic systems. The definitions, summaries, and comparisons are relevant to novice robotics engineers and embedded system developers seeking a primer of available algorithms.

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Section: Ant Colony Algorithmmentioning

confidence: 99%

A Survey of Path Planning Algorithms for Mobile Robots

et al. 2021

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“…The adaptive ant colony algorithm proposed in the literature [42][43][44] adaptively controls the proportion of pheromone concentration in the current optimal solution and updates the global pheromone concentration of the optimal path in real time by introducing a hyperbolic sine function as an adaptive dynamic factor σ(σ ∈ (0, 1)). In this way, the path exploration results can be effectively implemented when the performance of each path is known.…”

Section: Global Dynamic Selection Of Pathmentioning

confidence: 99%

Path Planning Strategy for Vehicle Navigation Based on User Habits

et al. 2018

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Vehicle navigation is widely used in path planning of self driving travel, and it plays an increasing important role in people's daily trips. Therefore, path planning algorithms have attracted substantial attention. However, most path planning methods are based on public data, aiming at different driver groups rather than a specific user. Hence, this study proposes a personalized path decision algorithm that is based on user habits. First, the categories of driving characteristics are obtained through the investigation of public users, and the clustering results corresponding to the category space are obtained by log fuzzy C-means clustering algorithm (LFCM) based on the driving information contained in the log trajectories. Then, the road performance personalized quantization algorithm evaluation is proposed to evaluate roads from the user's field of vision. Finally, adaptive ant colony algorithm is improved and used to validate the path planning based on the road performance personalized values. Results show that the algorithm can meet the personalized requirements of the user path selection in the path decision.

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Identification of Suitable FMRP Using Inverse Ant Algorithm for Caraga Region

Jayoma

Torres

2021

TENCON 2021 - 2021 IEEE Region 10 Conference (TENCON)

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A solution for simultaneous adaptive ant colony algorithm to memory demand vehicle routing problem with pickups

Cited by 3 publications

References 3 publications

A Survey of Path Planning Algorithms for Mobile Robots

A Survey of Path Planning Algorithms for Mobile Robots

Path Planning Strategy for Vehicle Navigation Based on User Habits

Identification of Suitable FMRP Using Inverse Ant Algorithm for Caraga Region

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