A multi-layer congested facility location problem with consideration of impatient customers in a queuing system

Chaleshtori, Amir Eshaghi; Jahani, Hamed; Aghaie, Abdollah; Ivanov, Dmitry

doi:10.1016/j.ifacol.2019.11.545

Cited by 8 publications

(3 citation statements)

References 20 publications

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“… Asghari et al (2020) and Karimi-Mamaghan et al (2020) revealed that the NSGA-II is an excellent evolutionary algorithm and a powerful yet simple method to solve a bi-objective problem. The NSGA-II method holds a broad application to resolve theoretical and practical models ( Chaleshtori et al, 2019 ). Algorithm 1 introduces the steps of the NSGA-II approach in which a population consisting of competing individuals is generated first.…”

Section: Solution Methodologymentioning

confidence: 99%

COVID-19 vaccine distribution planning using a congested queuing system—A real case from Australia

Jahani¹,

Chaleshtori²,

Khaksar³

et al. 2022

Transportation Research Part E: Logistics and Transportation Re

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Section: Solution Methodologymentioning

confidence: 99%

COVID-19 vaccine distribution planning using a congested queuing system—A real case from Australia

Jahani¹,

Chaleshtori²,

Khaksar³

et al. 2022

Transportation Research Part E: Logistics and Transportation Re

Self Cite

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“…Their results suggest that a city where these three types of facilities are close to one another is not always desirable. Chaleshtori et al 9 . proposed a model to simultaneously minimize the waiting time for users and the idleness of a facility.…”

Section: Introductionmentioning

confidence: 99%

“…Their results suggest that a city where these three types of facilities are close to one another is not always desirable. Chaleshtori et al 9 proposed a model to simultaneously minimize the waiting time for users and the idleness of a facility. Sakurai et al 10 constructed a model in which the location and size of a retail zone are changed according to the trip-chaining behavior of consumers and simulated the location of the retail zone.…”

Section: Introductionmentioning

confidence: 99%

A model to optimize the location and size of facilities based on the area of the facility and the visit time of users

Tsunoda

Yoshikawa

2023

Japan Architectural Review

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This paper proposes a new model to optimize the location and size of facilities that serve the public. The objective function is based on the floor area of the facility and the time that individuals spend in the facility. In this model, the area is used to represent the range of services provided by the facility: the larger the area, the more services are available, and thus the greater the utility. Time spent is based on daily time use and represents the degree to which users could enjoy the services provided: If the time spent in the facility is short, users are unable to take full advantage of the services offered. Focusing on the actual time spent makes it possible to avoid an overestimation of the facility's utility. The proposed model is applied to both a virtual city and an actual city. The results indicate that the optimum size of a facility depends on the amount of time that users can spend in the facility without restriction and that the optimum location is influenced by user activity patterns and population distribution. This suggests that planners should survey the daily time use of potential users before integrating facilities.

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Reconfigurable and Resilient Closed-Loop Supply Chain Design: A Simulation–Optimization Approach

Gholizadeh,

Pasha,

Hejazi

et al. 2024

Glob J Flex Syst Manag

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A multi-layer congested facility location problem with consideration of impatient customers in a queuing system

Cited by 8 publications

References 20 publications

COVID-19 vaccine distribution planning using a congested queuing system—A real case from Australia

COVID-19 vaccine distribution planning using a congested queuing system—A real case from Australia

A model to optimize the location and size of facilities based on the area of the facility and the visit time of users

Reconfigurable and Resilient Closed-Loop Supply Chain Design: A Simulation–Optimization Approach

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