Path Choice of Emergency Logistics Based on Cumulative Prospect Theory

Zhu, Changfeng; Zhang, Zheng-kun; Wang, Qingrong

doi:10.1155/2019/8512423

Cited by 12 publications

(2 citation statements)

References 27 publications

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“…The experimental results indicated that the route optimization strategy considering road slope reduced vehicle route costs, indicating the correctness of considering vehicle load and road slope factors in transportation logistics. Zhu et al [15] constructed an emergency logistics route selection model based on cumulative prospect theory, integrating path attributes and decision-makers' risk attitudes into the decisionmaking model. The model also analyzed the decision-making behavior of the decisionmakers.…”

Section: Related Workmentioning

confidence: 99%

An Intelligent Connected Vehicle Material Distribution Route Model Based on k-Center Spatial Cellular Clustering and an Improved Cockroach Optimization Algorithm

Zhou,

Wang,

Liu

et al. 2024

Symmetry

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Based on the analysis of the problems in material distribution routes, we propose the idea of integrating the intelligent connected vehicle system with material distribution, and construct an intelligent connected vehicle material distribution route model based on k-center spatial cellular clustering and an improved cockroach optimization algorithm. Firstly, we set the research scope to include the distribution center, the distribution points and the geographical environment. A cellular spatial model of distribution points is constructed to quantify and visualize the neighborhood relationship between the distribution centers and distribution points. On this basis, we construct an intelligent connected vehicle material distribution route model based on the improved cockroach optimization algorithm, and the optimal material distribution center is determined by searching for the corresponding optimal distribution route of each distribution center. In the experiment, we use the concept of symmetry to design routes that start from the initial points. The route passes through the distribution point, and finally reaches the destination. In this mode, the experiment generates symmetrically round-trip routes and generates different distribution time schedules. Case studies and comparative experiments show that the proposed algorithm has a total distance cost 1.2 km lower than the distance cost generated by the Baidu Map method and 2.7 km lower than the distance cost generated by the 360 Map method. In terms of the total time cost of the proposed algorithm, it is 0.06 h lower than the time cost generated by the Baidu Map method and 0.135 h lower than the time cost generated by the 360 Map method. Compared with the commonly used Dijkstra algorithm and the A* algorithm for route optimization, our proposed algorithm also generates a lower cost than the two other types of optimization algorithms. In the case study, the distance generated by the proposed algorithm is 1.8 km lower than that of the Dijkstra algorithm, and the total time cost is 0.09 h lower than that of the Dijkstra algorithm. The distance generated by the proposed algorithm is 1.6 km lower than that of the A* algorithm, and the total time cost is 0.08 h lower than that of the A* algorithm. Meanwhile, the proposed algorithm has a lower time complexity than the two commonly used optimization algorithms. Therefore, our proposed algorithm can find the distribution route with the lowest transportation cost. Compared to the commonly used electronic maps and the optimization algorithms for distribution route planning, our proposed algorithm can output distribution routes with lower costs under the same distribution sequence, and reduce the transportation costs for intelligent connected vehicle material distribution systems to the maximum extent.

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Section: Related Workmentioning

confidence: 99%

An Intelligent Connected Vehicle Material Distribution Route Model Based on k-Center Spatial Cellular Clustering and an Improved Cockroach Optimization Algorithm

Zhou,

Wang,

Liu

et al. 2024

Symmetry

View full text Add to dashboard Cite

show abstract

“…With respect to the value of weight w l , some empowerment methods have been developed, such as fuzzy theory [34], group decision-making [35], and rough set theory [36]. In this paper, the entropy weight method is strongly recommended in that this method can effectively avoid decision errors caused by incomplete information [37,38]. Let A � (a ij ) |L|×n be an attribute matrix; herein, |L| is the number of rescheduled trains, and n is the number of attributes, such as train type, the importance of train path, and the number of interface stations.…”

Section: Optimization Model For Trep-based Dedsmentioning

confidence: 99%

Discrete Optimization on Train Rescheduling on Single-Track Railway: Clustering Hierarchy and Heuristic Search

Zhang

Zhu

2020

Journal of Advanced Transportation

Self Cite

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This paper focuses on discrete dynamic optimization on train rescheduling on single-track railway with the consideration of train punctuality and station satisfaction degree. A discrete dynamic system is firstly described to mimic train rescheduling, and a state transition function is specially designed according to the train departure event. The purpose of this function is to improve simulation efficiency by directly confirming the next discrete time. After the construction and analysis of optimization models to discrete dynamic system, a two-stage heuristic search strategy is developed, by using clustering hierarchy theory and stochastic search strategy, to obtain train departure time and arrival time before each state transition of the system. Finally, a numerical experiment is conducted to verify the proposed system, models, and the heuristic search strategy. The result shows that the discrete dynamic system, together with the state transition function and heuristic search strategy, shows better performance in simulation efficiency and solution quality.

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Measuring city sustainability and coupling coordinated performance in economy, society, environment, and governance in 52 northern Chinese cities

Wang,

Hou,

Zhu

2024

Environ Dev Sustain

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Path Choice of Emergency Logistics Based on Cumulative Prospect Theory

Cited by 12 publications

References 27 publications

An Intelligent Connected Vehicle Material Distribution Route Model Based on k-Center Spatial Cellular Clustering and an Improved Cockroach Optimization Algorithm

An Intelligent Connected Vehicle Material Distribution Route Model Based on k-Center Spatial Cellular Clustering and an Improved Cockroach Optimization Algorithm

Discrete Optimization on Train Rescheduling on Single-Track Railway: Clustering Hierarchy and Heuristic Search

Measuring city sustainability and coupling coordinated performance in economy, society, environment, and governance in 52 northern Chinese cities

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