A Multi-objective Imperialist Competitive Algorithm for a Capacitated Single-allocation Hub Location Problem

Moghaddam, Reza Tavakkoli; Kanani, Yousef Gholipour; Shahramifar, M

doi:10.5829/idosi.ije.2013.26.06c.06

Cited by 6 publications

(3 citation statements)

References 39 publications

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“…A variety of are reviewed in articles. Some of the most attractive solving methods are as follows: Tavakkoli-Moghadam et al [16] developed a multiobjective mathematical model for a capacitated single hub location problem to determine the location and the capacity of hub node. The model is solved by a multiobjective imperialist competitive algorithm.…”

Section: Literature Reviewmentioning

confidence: 99%

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Development of a Model for Locating Hubs in a Competitive Environment under Uncertainty: A Robust Optimization Approach

Nourzadeh

Ebrahimnejad

Khalili‐Damghani

et al. 2020

IJE

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This article explores the development of previous models to determine hubs in a competitive environment. In this paper, by comparing parameters of the ticket price, travel time and the service quality of hub airports, airline hubs are divided into six categories. The degree of importance of travel time and travel cost are determined by a multivariate Lagrange interpolation method, which can play an important role in allocating travelers to follower airline hubs. Then, based on the seasonal demand of travelers, we consider travel demand as uncertain parameters. To determine the robust counterpart of this category of hub location models, a robust optimization method is used. Finally, models are tested in a case study. The central results show that the follower airline's income has a considerable growth and can absorb nearly 2% of travelers of the leader airline due to lower travel costs and travel time compared to that of leader airline.

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Section: Literature Reviewmentioning

confidence: 99%

“…( 1 , 1 , ⋯ , ) = ∑ .1≤ (16) where = ( 1 , ⋯ , ) and ∑ =1 = 1. In order to uniquely determine , we require = ( + ) independent points in Equation (17).…”

Section: Determining the Importance Of Travel Time Travel Cost And Smentioning

confidence: 99%

Development of a Model for Locating Hubs in a Competitive Environment under Uncertainty: A Robust Optimization Approach

Nourzadeh

Ebrahimnejad

Khalili‐Damghani

et al. 2020

IJE

View full text Add to dashboard Cite

show abstract

“…They may appear after the schedule has been prepared, which necessitates corrections. All this makes it difficult to coordinate production in time [1][2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

The concept of algorithm supporting the process of scheduling production tasks

2018

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The purpose of the work was to develop a concept of an algorithm which supports the process of scheduling production tasks. The designed algorithm performs a task queue creation process in six steps: selecting a schedule type, declaring a queue length, selecting orders for queue development, loading data, automatic job analysis, and queue and Gantt chart generation, taking a decision on the acceptance of the designed production program. The designed system will use single-attribute priority rules (defined by experts) and multi-attribute rules that can be created by combining single-attribute rules. The concept of an algorithm that supports the process of scheduling production tasks, developed and tested by conducting simulations, can be the basis for developing a computer application supporting decision-making process in a manufacturing or service company.

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Integration of multi-product supply chain network design and assembly line balancing

Ramezanian

Khalesi

2019

Oper Res Int J

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A Multi-objective Imperialist Competitive Algorithm for a Capacitated Single-allocation Hub Location Problem

Cited by 6 publications

References 39 publications

Development of a Model for Locating Hubs in a Competitive Environment under Uncertainty: A Robust Optimization Approach

Development of a Model for Locating Hubs in a Competitive Environment under Uncertainty: A Robust Optimization Approach

The concept of algorithm supporting the process of scheduling production tasks

Integration of multi-product supply chain network design and assembly line balancing

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