Hierarchical structure modelling in uncertain emergency location-routing problem using combined genetic algorithm and simulated annealing

Nahavandi, Bijan; Homayounfar, Mahdi; Daneshvar, Amir; Shokouhifar, Mohammad

doi:10.1504/ijcat.2022.123466

Cited by 6 publications

(3 citation statements)

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“…These algorithms can be applied to large-scale and complex problems and are often inspired by natural phenomena. Genetic Algorithms [21][22][23][24][25][26][27] algorithms are inspired by the process of natural selection and evolution. They use a population of candidate solutions that evolve over time through mutation, crossover, and selection operations.…”

Section: Literature Reviewmentioning

confidence: 99%

A mixed-integer linear optimization problem for highway emergency vehicle routing

Wang,

Tian,

et al. 2023

Eighth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023)

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Section: Literature Reviewmentioning

confidence: 99%

A mixed-integer linear optimization problem for highway emergency vehicle routing

Wang,

Tian,

et al. 2023

Eighth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023)

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“…The rescue status and rescue areas of the tourist attraction rescue zones were determined based on the rewards of all rescue zones. Taking into account the reliability of the facility system, Nahavandi established an emergency logistics location-routing model to maximize the reliability of the facility system and ensure that the emergency logistics system can respond to demands even when certain facilities are unable to operate [13]. In the scenario where multiple suppliers provide goods, Khanchehzarrin considered the risk of the goods and developed a multi-objective bi-level model for the emergency logistics location-routing problem [14].…”

Section: Introductionmentioning

confidence: 99%

Research on the Deployment of Professional Rescue Ships for Maritime Traffic Safety under Limited Conditions

Shao,

Wu,

et al. 2024

JMSE

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This paper focuses on optimizing the deployment plan for standby points of professional rescue vessels based on the data of maritime incidents in the Beihai area of China. The primary objective is to achieve multi-level and multiple coverage of the jurisdictional waters of the Beihai Rescue Bureau. Models including the coverage quality of the jurisdictional waters, the coverage quality in high-risk areas, the maximum coverage of jurisdictional areas, and the maximum coverage of high-risk areas are constructed and solved using 0–1 integer programming. The optimal plan for eight standby points and their corresponding deployment plans for rescue vessels are obtained. A comparison with the current site selection plan of the Beihai Rescue Bureau validates the superiority of the proposed deployment plan for rescue vessel standby points in this paper.

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“…However, the uncertainty of emergency scenarios is still unavoidable, which stimulates the study of uncertainty. Nahavandi [17] put forward a hierarchical structure model with a combined genetic algorithm. The model solved the uncertain emergency location-routing problem with higher efficiency.…”

Section: Introductionmentioning

confidence: 99%

Scheduling Optimization of Mobile Emergency Vehicles Considering Dual Uncertainties

Li,

Fu,

Lai

et al. 2023

Applied Sciences

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Compared with the traditional operation mode of emergency vehicles, the mobile emergency vehicle is regarded as a new type of emergency facility carrier with the features of variable locations, flexible mobility, and intelligent decision-making. It can provide an effective solution to reasonably respond to the uncertain risks of sudden disasters. Focusing on meeting the maximum demand for materials and services in disaster areas, this paper proposes a scheduling model of mobile emergency vehicles with dual uncertainty of path and demand. The model, solved by an integer-coding hybrid genetic algorithm, aims to obtain minimum mobile emergency scheduling cost and time by transforming the multi-objective problem into a single-objective problem. The “5.12” Wenchuan earthquake is used as an example to validate the model and solving method. The results show that the model can reduce the impact of uncertain risks and improve the scientific logic of emergency strategies and deployments based on the actual crisis scenario. It benefits from introducing mobile emergency vehicles and optimizing their scheduling process.

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Hierarchical structure modelling in uncertain emergency location-routing problem using combined genetic algorithm and simulated annealing

Cited by 6 publications

References 0 publications

A mixed-integer linear optimization problem for highway emergency vehicle routing

A mixed-integer linear optimization problem for highway emergency vehicle routing

Research on the Deployment of Professional Rescue Ships for Maritime Traffic Safety under Limited Conditions

Scheduling Optimization of Mobile Emergency Vehicles Considering Dual Uncertainties

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