Location and path planning for urban emergency rescue by a hybrid clustering and ant colony algorithm approach

Yang, Bing; Wu, Lunwen; Xiong, Jian; Zhang, Yuxin; Chen, Lidong

doi:10.1016/j.asoc.2023.110783

Cited by 8 publications

(3 citation statements)

References 33 publications

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“…Wilcoxon rank sum test [43] is a nonparametric hypothesis test method, which compares whether there is a significant difference between two independent samples by using the value of significance level of 0.05. In this paper, the Wilcoxon rank sum test is used to compare CMISSA with 10 other intelligent algorithms, and the results are shown in table 5. Where p-value is used to judge whether to reject the null hypothesis.…”

Section: Discussionmentioning

confidence: 99%

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A multi-strategy improved sparrow search algorithm for mobile robots path planning

Fan,

2024

Meas. Sci. Technol.

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Path planning for mobile robots plays a vital role in task execution, given the constraints imposed by environments and energy resources. It poses a significant challenge for mobile robots, requiring them to find a feasible path between the start point and target point that is obstacle-free and as short as possible. To address the challenge of path planning, a multi-strategy improved sparrow search algorithm with crazy operator (CMISSA) is proposed. Firstly, Tent chaos mapping and reverse learning are introduced into the population initialization of sparrow search algorithm (SSA) to enhance the uniformity and effectiveness of the initial population distribution. Secondly, adaptive parameters are applied in SSA to maintain a balance between exploitation and exploration. Thirdly, to prevent SSA from getting trapped in local optima, the crazy operator is used to perturb the population position. Finally, a novel adaptive boundary control strategy is introduced to handle the location of individuals that have crossed the boundary. In addition, the experimental results on 15 classical benchmark functions show that CMISSA has better optimization performance than other 10 comparison algorithms. Furthermore, in the path planning experimental results, the results of comparing CMISSA with 5 comparison algorithms on 5 different environments reveal CMISSA's average path shortening rates were 34.90%, 20.11%, 29.01%, 51.97%, 37.42%, respectively. It is further demonstrated that CMISSA has superior availability for solving mobile robots path planning.

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Section: Discussionmentioning

confidence: 99%

“…Mobile robots are used extensively in rescue [1,2], nuclear power plant inspections [3,4], intelligent agriculture [5,6], and many other fields. Planning a proper path is necessary for a mobile robot to accomplish a task.…”

Section: Introductionmentioning

confidence: 99%

A multi-strategy improved sparrow search algorithm for mobile robots path planning

Fan,

2024

Meas. Sci. Technol.

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“…The existing emergency rescue dispatch methods mainly focus on the path planning of rescue vehicles and rescue locations [4], [5]. As a key part of the urban emergency defense system, the selection of rescuers and rescue vehicles is very important, and most of them only consider the impact of the characteristics of electric vehicles on rescue [6], while ignoring the comprehensive quality expected by rescuers.…”

Section: Headingmentioning

confidence: 99%

A Multi-Objective Power Grid Fault Emergency Rescue Method Based on Human-Vehicle Feature Matching

Zhang,

Chen

2024

Advances in Transdisciplinary Engineering

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With the popularization and extensive use of power grid, people’s lives and many factories generally rely on electricity, and once the power grid is damaged and fails, it will seriously endanger the social order and economic benefits. At present, the research on the rescue dispatch of electric vehicles as an emergency power source mainly focuses on path planning, and does not consider the comprehensive rescue ability of the rescuers dispatched, nor does it involve the matching degree of rescuers and rescue vehicles. In this paper, the rescue urgency is obtained through the analysis and evaluation of the fault point, the characteristics of the rescue vehicles and rescue personnel are analyzed to screen out the appropriate rescue vehicles and personnel, the Euler distance is used to solve the matching coefficient between the rescue vehicle and the rescue personnel, and finally the multi-objective power grid fault emergency rescue function considering the matching of human and vehicle characteristics is established.

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Geographic Network Analysis

2024

Geographic Data Analysis Using R

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Location and path planning for urban emergency rescue by a hybrid clustering and ant colony algorithm approach

Cited by 8 publications

References 33 publications

A multi-strategy improved sparrow search algorithm for mobile robots path planning

A multi-strategy improved sparrow search algorithm for mobile robots path planning

A Multi-Objective Power Grid Fault Emergency Rescue Method Based on Human-Vehicle Feature Matching

Geographic Network Analysis

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