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Road screening and distribution route multi-objective robust optimization for hazardous materials based on neural network and genetic algorithm

Author

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  • Changxi Ma
  • Wei Hao
  • Fuquan Pan
  • Wang Xiang

Abstract

Route optimization of hazardous materials transportation is one of the basic steps in ensuring the safety of hazardous materials transportation. The optimization scheme may be a security risk if road screening is not completed before the distribution route is optimized. For road screening issues of hazardous materials transportation, a road screening algorithm of hazardous materials transportation is built based on genetic algorithm and Levenberg–Marquardt neural network (GA-LM-NN) by analyzing 15 attributes data of each road network section. A multi-objective robust optimization model with adjustable robustness is constructed for the hazardous materials transportation problem of single distribution center to minimize transportation risk and time. A multi-objective genetic algorithm is designed to solve the problem according to the characteristics of the model. The algorithm uses an improved strategy to complete the selection operation, applies partial matching cross shift and single ortho swap methods to complete the crossover and mutation operation, and employs an exclusive method to construct Pareto optimal solutions. Studies show that the sets of hazardous materials transportation road can be found quickly through the proposed road screening algorithm based on GA-LM-NN, whereas the distribution route Pareto solutions with different levels of robustness can be found rapidly through the proposed multi-objective robust optimization model and algorithm.

Suggested Citation

  • Changxi Ma & Wei Hao & Fuquan Pan & Wang Xiang, 2018. "Road screening and distribution route multi-objective robust optimization for hazardous materials based on neural network and genetic algorithm," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-22, June.
  • Handle: RePEc:plo:pone00:0198931
    DOI: 10.1371/journal.pone.0198931
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    References listed on IDEAS

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    Cited by:

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    6. Wang, Chao & Ma, Changxi & Xu, Xuecai(Daniel), 2020. "Multi-objective optimization of real-time customized bus routes based on two-stage method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    7. Ma, Xinjuan & Ge, Hongxia & Cheng, Rongjun, 2019. "Influences of acceleration with memory on stability of traffic flow and vehicle’s fuel consumption," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 143-154.
    8. Chen, Can & Cheng, Rongjun & Ge, Hongxia, 2019. "An extended car-following model considering driver’s sensory memory and the backward looking effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 278-289.
    9. Huimin Liu & Yuhong Wang, 2021. "Impact of Strong Wind and Optimal Estimation of Flux Difference Integral in a Lattice Hydrodynamic Model," Mathematics, MDPI, vol. 9(22), pages 1-13, November.
    10. Zhaoze, Liu & Rongjun, Cheng & Hongxia, Ge, 2019. "Research on preceding vehicle’s taillight effect and energy consumption in an extended macro traffic model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 304-314.
    11. Sheng Dong & Jibiao Zhou & Changxi Ma, 2020. "Design of a Network Optimization Platform for the Multivehicle Transportation of Hazardous Materials," IJERPH, MDPI, vol. 17(3), pages 1-14, February.
    12. Changxi Ma & Jibiao Zhou & Dong Yang, 2020. "Causation Analysis of Hazardous Material Road Transportation Accidents Based on the Ordered Logit Regression Model," IJERPH, MDPI, vol. 17(4), pages 1-25, February.
    13. Qi, Xinyue & Ge, Hongxia & Cheng, Rongjun, 2019. "Analysis of a novel lattice hydrodynamic model considering density integral and “backward looking” effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 714-723.
    14. Hongxia Ge & Siteng Li & Chunyue Yan, 2021. "An Extended Car-Following Model Based on Visual Angle and Electronic Throttle Effect," Mathematics, MDPI, vol. 9(22), pages 1-17, November.
    15. Li, Lixiang & Cheng, Rongjun & Ge, Hongxia, 2021. "New feedback control for a novel two-dimensional lattice hydrodynamic model considering driver’s memory effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 561(C).
    16. Li Zhou & Chun Guo & Yunxiao Cui & Jianjun Wu & Ying Lv & Zhiping Du, 2020. "Characteristics, Cause, and Severity Analysis for Hazmat Transportation Risk Management," IJERPH, MDPI, vol. 17(8), pages 1-24, April.
    17. Xiaoqiu Shi & Wei Long & Yanyan Li & Dingshan Deng, 2020. "Multi-population genetic algorithm with ER network for solving flexible job shop scheduling problems," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-23, May.
    18. Xiuguang Song & Jianqing Wu & Hongbo Zhang & Rendong Pi, 2020. "Analysis of Crash Severity for Hazard Material Transportation Using Highway Safety Information System Data," SAGE Open, , vol. 10(3), pages 21582440209, July.
    19. Chang, Yinyin & He, Zhiting & Cheng, Rongjun, 2019. "Analysis of the historical time integral form of relative flux and feedback control in an extended lattice hydrodynamic model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 326-334.
    20. Jianyu Wang & Huapu Lu & Zhiyuan Sun & Tianshi Wang, 2020. "Exploring Factors Influencing Injury Severity of Vehicle At-Fault Accidents: A Comparative Analysis of Passenger and Freight Vehicles," IJERPH, MDPI, vol. 17(4), pages 1-12, February.
    21. Ren, Weilin & Cheng, Rongjun & Ge, Hongxia, 2021. "Bifurcation analysis for a novel heterogeneous continuum model considering electronic throttle angle changes with memory," Applied Mathematics and Computation, Elsevier, vol. 401(C).
    22. Jiao, Yulei & Ge, Hongxia & Cheng, Rongjun, 2019. "Nonlinear analysis for a modified continuum model considering electronic throttle (ET) and backward looking effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).

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