When tested by a real world application, the results evince the accuracy of the models to reach a trade-off between operational costs and a given service level. This paper is structured as follows. Section 1 provides an insight on the problem terminology. Section 3 presents two optimization models to solve the ACCAP for common and dedicated check-in systems. Section 4 contains the case study and the results analysis. Finally, we take some conclusions about the work and identify future directions of research.
Airport Development Reference Manual, 9th Edition. International Air Transport Association. Arrival pattern: represents the proportion of passengers' arrival for check-in process, distributed by fixed time intervals. Check-in period: period before flight departure during which passengers are allowed to register for the flight.
It starts at Flight-open time and ends at Flight close-out time, after which the flight is said to be closed. Departure flight schedule: departure flights information indicating the number of flights, the number of passengers and the starting time interval for each flight.
Common check-in system: passengers can check-in for their flights at any available desk during the check-in period. Dedicated check-in system: specific position desks are assigned for each flight during the check-in period. Constant desks allocation policy: each flight is allocated to a constant number of desks during its check-in period.
Variable desks allocation policy: each flight is allocated to a variable number of desks in each time interval e. Service level: the customer satisfaction in terms of waiting time or queues size, specially. A brief description of each step and a flow chart Figure 1 about how works the methodology will be given in this section.
Considering the variable allocation policy, we present two new optimization models, one for a common check-in system and the other for a dedicated. They aim to determine the minimum number of check-in desks to be opened by time interval, such that operational costs and the quality of service are balanced. These models present a new service level constraint.
Step 1 is a deterministic scheduling problem based on the departure flight schedule, reference arrival pattern and a rough check-in time.
Second, Step 2 recurs to simulation ARENA software in order to assess if the results reached through Step 1 meet a given service level in terms of waiting and queue size when considering real uncertainty behavior.
So, they argue the importance of simulation in order to capture the non-steady behavior of the check-in process. In overall, the check-in process is studied considering the passenger arrival pattern for check-in service and how the passengers are served at the counters. In order to scrutinize the both passenger arrival and check-in time distributions, a set of scenarios are defined.
The main scenarios to be tested are the common and dedicated check-in systems. According to Chun and Wak Chun, H. Statistics of interest have to do with the waiting time and queue size. Third, in Step 3 once one has determined the required number of desks by time interval for each flight dedicated system it is possible to minimize the total number of desks under the adjacent constraint.
This constraint stipulates that all desks for the same flight should be adjacent. Duin and Van der Sluis Duin, C. On the complexity of Adjacent Resource Scheduling. This would indicate the maximum of required desks N max at the busiest time interval but it does not guarantee an optimal solution satisfying the adjacency constraint.
However, it is clear that N max is always the lower bound for the optimal number of required desks. In this way, mathematical models related with the adjacent constraint have to guarantee an optimal desk allocation with no more than N max desks.
Step 3 is a deterministic scheduling problem based on a given required number of desks for each flight with variable allocation policy. From a check-in desks management point of view, the objective is to determine the minimum number of check-in desks to be opened by time interval that ensures a given service level.
The desk allocation can be made following a constant or a variable policy. With the latter, peak hours will have more desks while off-peak will have less. Thus, the variable policy seems more reasonable and can lead to a more optimized solution. Room 3. More options. Category 2 stars 3 stars 4 stars 5 stars. Premier Selection. Offering Free Child Place. Spa Breaks. Single Parent Saver. Exclusive to Balkan Holidays. Allocation On Arrival.
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