Mine fire emergency path planning based on hybrid strategy improved WOA algorithm.
To address the challenge of personnel evacuation during mine fires, an enhanced Whale Optimization Algorithm (WOA) incorporating a hybrid strategy inspired by the intelligent behavior of marine life is proposed and applied to mine escape route planning. Initially, to overcome the limitations of the...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0323789 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849332140193349632 |
|---|---|
| author | Yun Qi Kaiwang Yu Xunping Li Wei Wang Xinchao Cui Chenhao Bai |
| author_facet | Yun Qi Kaiwang Yu Xunping Li Wei Wang Xinchao Cui Chenhao Bai |
| author_sort | Yun Qi |
| collection | DOAJ |
| description | To address the challenge of personnel evacuation during mine fires, an enhanced Whale Optimization Algorithm (WOA) incorporating a hybrid strategy inspired by the intelligent behavior of marine life is proposed and applied to mine escape route planning. Initially, to overcome the limitations of the original WOA-such as poor optimization accuracy, susceptibility to local optima, and slow convergence-five improvement strategies are introduced: Sobol sequence for population initialization, nonlinear time-varying factors, adaptive weighting, stochastic learning, and Cauchy mutation. These enhancements are compared against single-strategy improved WOAs.Subsequently, path planning simulations were conducted using several extracted algorithms and grid-based methods. The results demonstrate that the optimal path length achieved by the Multi-Strategy WOA (MSWOA) is 41.7% shorter than that of the standard WOA, 42.3% shorter than WOA-1, and 48.5% shorter than PSO for the shortest path. Additionally, the average path length of MSWOA is 32.2% shorter than WOA, 40.5% shorter than WOA-1, and 41.4% shorter than PSO. The MSWOA algorithm generates the shortest and smoothest path among the tested methods.Based on the analysis of the path graph and iteration frequency graph, it is recommended to apply the MSWOA algorithm to path planning experiments. The findings indicate that the WOA with the five integrated strategies significantly enhances optimization accuracy and convergence speed, making it a robust solution for mine evacuation route planning. |
| format | Article |
| id | doaj-art-c8afb007d0c44c989cdda64c80f0a552 |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-c8afb007d0c44c989cdda64c80f0a5522025-08-20T03:46:19ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01205e032378910.1371/journal.pone.0323789Mine fire emergency path planning based on hybrid strategy improved WOA algorithm.Yun QiKaiwang YuXunping LiWei WangXinchao CuiChenhao BaiTo address the challenge of personnel evacuation during mine fires, an enhanced Whale Optimization Algorithm (WOA) incorporating a hybrid strategy inspired by the intelligent behavior of marine life is proposed and applied to mine escape route planning. Initially, to overcome the limitations of the original WOA-such as poor optimization accuracy, susceptibility to local optima, and slow convergence-five improvement strategies are introduced: Sobol sequence for population initialization, nonlinear time-varying factors, adaptive weighting, stochastic learning, and Cauchy mutation. These enhancements are compared against single-strategy improved WOAs.Subsequently, path planning simulations were conducted using several extracted algorithms and grid-based methods. The results demonstrate that the optimal path length achieved by the Multi-Strategy WOA (MSWOA) is 41.7% shorter than that of the standard WOA, 42.3% shorter than WOA-1, and 48.5% shorter than PSO for the shortest path. Additionally, the average path length of MSWOA is 32.2% shorter than WOA, 40.5% shorter than WOA-1, and 41.4% shorter than PSO. The MSWOA algorithm generates the shortest and smoothest path among the tested methods.Based on the analysis of the path graph and iteration frequency graph, it is recommended to apply the MSWOA algorithm to path planning experiments. The findings indicate that the WOA with the five integrated strategies significantly enhances optimization accuracy and convergence speed, making it a robust solution for mine evacuation route planning.https://doi.org/10.1371/journal.pone.0323789 |
| spellingShingle | Yun Qi Kaiwang Yu Xunping Li Wei Wang Xinchao Cui Chenhao Bai Mine fire emergency path planning based on hybrid strategy improved WOA algorithm. PLoS ONE |
| title | Mine fire emergency path planning based on hybrid strategy improved WOA algorithm. |
| title_full | Mine fire emergency path planning based on hybrid strategy improved WOA algorithm. |
| title_fullStr | Mine fire emergency path planning based on hybrid strategy improved WOA algorithm. |
| title_full_unstemmed | Mine fire emergency path planning based on hybrid strategy improved WOA algorithm. |
| title_short | Mine fire emergency path planning based on hybrid strategy improved WOA algorithm. |
| title_sort | mine fire emergency path planning based on hybrid strategy improved woa algorithm |
| url | https://doi.org/10.1371/journal.pone.0323789 |
| work_keys_str_mv | AT yunqi minefireemergencypathplanningbasedonhybridstrategyimprovedwoaalgorithm AT kaiwangyu minefireemergencypathplanningbasedonhybridstrategyimprovedwoaalgorithm AT xunpingli minefireemergencypathplanningbasedonhybridstrategyimprovedwoaalgorithm AT weiwang minefireemergencypathplanningbasedonhybridstrategyimprovedwoaalgorithm AT xinchaocui minefireemergencypathplanningbasedonhybridstrategyimprovedwoaalgorithm AT chenhaobai minefireemergencypathplanningbasedonhybridstrategyimprovedwoaalgorithm |