A model to optimize the airport terminal departure operations

Adacher, Ludovica; Flamini, Marta; Guaita, Manuele; Romano, Elpidio

doi:10.1016/j.trpro.2017.12.151

Cited by 15 publications

(12 citation statements)

References 9 publications

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“…In the static procedure, η k varied from 0.01 to 0.9 with step 0.01, whereas the choice of the dynamic procedure is reported in Table 3, where five different options are examined. (1) Initialize ρ 0 � z 0 satisfying constraints [25,26] (ρ 0 is a continuous vector, z 0 is a discrete vector, both of dimension M + 1) (2) Initialize ρ * � ρ 0 , z * � z 0 (ρ * is the optimal solution of the continuous problem) (3) Initialize h � 0 (4) while ((k ≤ K) ∨ (h ≤ H)) do (K and H integer parameters, Form the selection set S(ρ k ) (steps 5-13): S(ρ k ) is a set of discrete vectors) [29], where ∇ j OF(ρ k ) � OF(p) − OF(q), where k satisfies p − q � e j and p, q ∈ S(ρ k ), Update state) (16) ρ k+1 � f[ρ k − η k ∇OF(ρ k )] (η k is the step size of the gradient method, Optimal solution update) (17) if OF(ρ k ) ≤ OF(ρ * ) then (18) ρ * � ρ k (19) h � 0 (20) else (21) h � h + 1 (22) end if (23) end while (Return the optimal solution z * ) (24) Return z * � arg min z k OF(z k ) ALGORITHM 1: e Surrogate Method.…”

Section: Results Analysismentioning

confidence: 99%

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Optimizing Airport Land Side Operations: Check-In, Passengers’ Migration, and Security Control Processes

Adacher

Flamini

2020

Journal of Advanced Transportation

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This paper deals with the optimization of the Check-in, passenger migration, and Security Control processes in an airport land side terminal. Given the layout of the terminal, the passengers’ flow, and the scheduled flights in a given time interval, the number and the position of Check-in counters and Security Control gates to be opened are output. The objective function is the minimization of the costs to activate the Check-in counters and the Security Control gates plus the costs that measure the passengers’ discomfort. The stochastic passengers’ behaviour and their preferences are simulated by a discrete event model, while the managing costs and the passengers’ discomfort are optimized by the Surrogate Method. Capodichino Airport, located in Naples (IT), has been considered for the test phase. Results show the effectiveness and efficiency of the solutions of the Surrogate Method compared with the performances of other algorithms.

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Section: Results Analysismentioning

confidence: 99%

“…e Surrogate Method provides good results in various application areas finding good or suboptimal solutions for the original discrete problem and assuring very fast convergence [25][26][27][28]. In a previous work [29], the authors firstly test the…”

Section: Optimization Module: the Surrogate Methodsmentioning

confidence: 99%

Optimizing Airport Land Side Operations: Check-In, Passengers’ Migration, and Security Control Processes

Adacher

Flamini

2020

Journal of Advanced Transportation

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“…In literature, some works dealing with uncertainty when planning airport expansion and developments use diverse methodologies, ranging from mathematical programming to simulation. In [6], an algorithm for determining the required number of airport terminal resources for a departing process, such as check-in desks and security controls, was presented. In this algorithm, the objective function did not have a closed-form expression so, for that reason, simulation was included in order to calculate it.…”

Section: Literature Reviewmentioning

confidence: 99%

Simulation-Based Virtual Cycle for Multi-Level Airport Analysis

et al. 2018

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The aeronautical industry is expanding after a period of economic turmoil. For this reason, a growing number of airports are facing capacity problems that can sometimes only be resolved by expanding infrastructure, with the inherent risks that such decisions create. In order to deal with uncertainty at different levels, it is necessary to have relevant tools during an expansion project or during the planning phases of new infrastructure. This article presents a methodology that combines simulation approaches with different description levels that complement each other when applied to the development of a new airport. The methodology is illustrated with an example that uses two models for an expansion project of an airport in The Netherlands. One model focuses on the operation of the airport from a high-level position, while the second focuses on other technical aspects of the operation that challenge the feasibility of the proposed configuration of the apron. The results show that by applying the methodology, analytical power is enhanced and the risk of making the wrong decisions is reduced. We identified the limitations that the future facility will have and the impact of the physical characteristics of the traffic that will operate in the airport. The methodology can be used for tackling different problems and studying particular performance indicators to help decision-makers take more informed decisions.

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“…In an attempt to address the queue problem, [7] were of the opinion that doubling service demand in queue situations does not necessarily require resources increase to achieve better performance. Another group of researchers, [8], investigated the number of critical resources at the first two phases of the airport departure operations and found that most passengers are not satisfied with the services received at the airport check-in process. Similarly, [9], applied the Discrete Event Simulation (DES) model to evaluate how arrival patterns of passengers to the airport departure hall affects international terminal operations such as check-in, security screening and immigration control.…”

Section: Introductionmentioning

confidence: 99%

Simulation of a Model for International Traveler’s Check-In Process Using Arena Software Tool

Obetta¹,

Olusanyan²,

Oyediran³

et al. 2021

ENG

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With the current situation of insecurity in Nigeria and the worsening condition of Nigerian roads, there is increasing demand for air travel. This increasing demand for airline services amidst limited resources results in passenger dissatisfaction and reduction of revenue for airports and airlines. The dynamics of service demand and resource supply result in check-in issues for all the stakeholders in the commercial aviation industry. Hence, this research simulated the developed model for travelers' check-in process at the "D Wing" of the Departure Section of Murtala Muhammed International Airport (MMIA), Ikeja, using Arena Software Tool. The simulation of the developed model was carried out by varying five different configurations of the servers with respect to the baggage weighing machines and passenger profiling devices to obtain the minimum average check-in time (ACT) for the process, with each configuration undergoing 133 completions of simulation runs. The result of the experimentation revealed that the 3 × 3 × 4 configuration of servers produced the smallest ACT of 18.25 minutes. This translates to a difference of about 58 minutes from the 76.16 minutes ACT of the real system; representing about 76% improvement in the check-in time of passengers. This study contributed to knowledge by revealing that the main choke points in the MMIA check-in system occur at the baggage weighing and passenger profiling areas as against the check-in counter subsection as advanced by previous works. Furthermore, the research added value to knowledge by creating a balance between customer satisfaction and cost of operations thereby accommodating the interests of the passenger and the operator who are the two main stakeholders in the commercial aviation industry.

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A model to optimize the airport terminal departure operations

Cited by 15 publications

References 9 publications

Optimizing Airport Land Side Operations: Check-In, Passengers’ Migration, and Security Control Processes

Optimizing Airport Land Side Operations: Check-In, Passengers’ Migration, and Security Control Processes

Simulation-Based Virtual Cycle for Multi-Level Airport Analysis

Simulation of a Model for International Traveler’s Check-In Process Using Arena Software Tool

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