An Analytical Optimisation Framework for Airport Terminal Capacity Expansion

This article considers how to allocate additional physical resources within airport terminals. An optimization model was developed to determine where additional resources should be placed to minimise passenger waiting times. The objective function is stochastic and can only be evaluated using discre...

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Main Authors: Sultan Alodhaibi, Robert L. Burdett, Prasad K. D. V. Yarlagadda
Format: Article
Language:English
Published: Wiley 2020-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2020/2976281
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author Sultan Alodhaibi
Robert L. Burdett
Prasad K. D. V. Yarlagadda
author_facet Sultan Alodhaibi
Robert L. Burdett
Prasad K. D. V. Yarlagadda
author_sort Sultan Alodhaibi
collection DOAJ
description This article considers how to allocate additional physical resources within airport terminals. An optimization model was developed to determine where additional resources should be placed to minimise passenger waiting times. The objective function is stochastic and can only be evaluated using discrete event simulation. As this model is stochastic and nonlinear, a Simulated Annealing (SA) metaheuristic was implemented and tested. The SA algorithm repeatedly perturbs a resource allocation solution using one of two methods. The first method is creating new solution randomly in each iteration, and the second method is local search that is mimicked by any move of the current solution of x solution chosen randomly in its neighborhood. Numerical testing shows that the random approach is best, and solutions that are 12.11% better can be obtained.
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institution Kabale University
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publishDate 2020-01-01
publisher Wiley
record_format Article
series Complexity
spelling doaj-art-bb4041f7559b4151ab2d4b8d634117502025-02-03T01:05:11ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/29762812976281An Analytical Optimisation Framework for Airport Terminal Capacity ExpansionSultan Alodhaibi0Robert L. Burdett1Prasad K. D. V. Yarlagadda2Department of Mathematics, College of Sciences and Arts in Al-Rass, Qassim University, Buraidah 51921, Saudi ArabiaSchool of Mathematical Science, Science and Engineering Faculty, Queensland University of Technology, Brisbane, QLD 4001, AustraliaSchool of Mechanical Medical and Process Engineering, Science and Engineering Faculty, Queensland University of Technology, Brisbane, QLD 4001, AustraliaThis article considers how to allocate additional physical resources within airport terminals. An optimization model was developed to determine where additional resources should be placed to minimise passenger waiting times. The objective function is stochastic and can only be evaluated using discrete event simulation. As this model is stochastic and nonlinear, a Simulated Annealing (SA) metaheuristic was implemented and tested. The SA algorithm repeatedly perturbs a resource allocation solution using one of two methods. The first method is creating new solution randomly in each iteration, and the second method is local search that is mimicked by any move of the current solution of x solution chosen randomly in its neighborhood. Numerical testing shows that the random approach is best, and solutions that are 12.11% better can be obtained.http://dx.doi.org/10.1155/2020/2976281
spellingShingle Sultan Alodhaibi
Robert L. Burdett
Prasad K. D. V. Yarlagadda
An Analytical Optimisation Framework for Airport Terminal Capacity Expansion
Complexity
title An Analytical Optimisation Framework for Airport Terminal Capacity Expansion
title_full An Analytical Optimisation Framework for Airport Terminal Capacity Expansion
title_fullStr An Analytical Optimisation Framework for Airport Terminal Capacity Expansion
title_full_unstemmed An Analytical Optimisation Framework for Airport Terminal Capacity Expansion
title_short An Analytical Optimisation Framework for Airport Terminal Capacity Expansion
title_sort analytical optimisation framework for airport terminal capacity expansion
url http://dx.doi.org/10.1155/2020/2976281
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