Event‐based allocation of airline check‐in counters: a simple dynamic optimization method supported by empirical data

Abstract

This paper studies the real‐life problem of dynamically optimizing the number of airport check‐in counters to allocate for a single flight. The main feature of our work is the use of empirical data collected at the Singapore Changi Airport, which drives the dynamic optimization model of a parallel queues system. We propose an event‐based dynamic programming model that simplifies considerably the optimization analysis even for large‐scale problems with 700+ booked passengers. We investigate the following research questions: (a) For a particular flight, what is the optimal number of counters the system should open with and what is the corresponding optimal total cost? (b) Given the state of the system at any event epoch, should we open another counter or not and what is the optimal cost‐to‐go from this state? The empirical data we collected at the airport are used to test the assumptions, estimate the key parameters, and run the computational experiments. We apply our model to 14 flights at the Singapore Changi Airport and identify cases in which, depending on the cost parameters, the model advocates the use of either a dynamic or a static policy. Although the model concerns only an exclusive‐use system, it is flexible enough to apply to other configurations such as a common‐use system or a single‐queue, multicounter system.

The value of flexible flight-to-route assignments in pre-tactical air traffic management

“…In Parlar et al (2018), the authors discuss a similar setting when modeling the arrival of customers to exclusive-use airline check-in counters, where customers can only use certain counters to check in for their flight. As in our setting, the authors expect most (if not all) passengers of a flight to arrive to check-in before the counter closes.…”

“…In Parlar et al (2018), the authors estimate 𝜆 𝐺 𝑡 based on historic arrival patterns. Let 𝜏 0 < 𝜏 1 < 𝜏 2 < ⋯ < 𝜏 𝑚 be the points in time (i.e., epochs) during which individual arrivals of scheduled flights occured in one such historic arrival pattern, and let 𝑞(𝑡) specify the last epoch before time 𝑡.…”

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

“…e objective is the minimization of the total cost of waiting counter operations and passenger delay. An improvement has been proposed in [15] where the authors consider the queuing optimization while developing a stochastic dynamic programming model able to determine the optimal numbers of counters to open in a given time window. In [16], the authors consider a more complex and complete problem suggesting a novel methodology which combines an evolutionary algorithm and simulation.…”