2021
DOI: 10.1002/cpe.6263
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The forecasting of air transport passenger demands in Turkey by using novel meta‐heuristic algorithms

Abstract: The imbalance between modes of transport in our country appears as the most important problem. Therefore, in air transportation, which has a significant increasing trend, estimating the passenger demand with directly related parameters and novel algorithms is important for Turkey. In this study, different prediction models were developed applying for the first time with five different meta-heuristic algorithms which are Flower Pollination Algorithm (FPA), Artificial Bee Colony Algorithm (ABC), Crow Search Algo… Show more

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Cited by 13 publications
(3 citation statements)
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“…The Bee Algorithm (BA) and its closely related variant, the Artificial Bee Colony (ABC), have demonstrated successful applications in various optimization problems. They have been particularly effective in domains such as vehicle routing and transportation, as exemplified by [21][22][23][24], as well as in timetabling and scheduling problems, as demonstrated in [25][26][27].…”
Section: Bees Algorithm (Ba)mentioning
confidence: 99%
“…The Bee Algorithm (BA) and its closely related variant, the Artificial Bee Colony (ABC), have demonstrated successful applications in various optimization problems. They have been particularly effective in domains such as vehicle routing and transportation, as exemplified by [21][22][23][24], as well as in timetabling and scheduling problems, as demonstrated in [25][26][27].…”
Section: Bees Algorithm (Ba)mentioning
confidence: 99%
“…Long-distance multimodal travel inside urban agglomerations or between them has increased significantly; this has increased requirements for multimodal transportation systems' operating effectiveness. The study of multimodal transport modes [1] and the sharing rate of each mode in longdistance travel [2] related to transportation networks is a priority, and the study of longdistance travel mode choice, transfer choices and travel costs related to individual choices is another [3][4][5].A major source of concern for policymakers is the forecast of passenger flow between significant cities [6] as well as the demand for travel by air [7] and high-speed railway [8] in megacities.…”
Section: Introductionmentioning
confidence: 99%
“…The operations planning process can be classified into strategic (long term), tactical (medium term), and operational (short term), depending on the planning horizon involved. Examples of strategic planning include the logistics network configuration and planning based on long‐term demand forecasting (Korkmaz and Akgüngör, 2021; Leandro et al., 2021) (e.g., several years), and mapping the needs of the airports and their best locations and capacities. Examples of tactical planning decisions are medium‐term flight scheduling to determine the best weekly or monthly flight timetable for an airline company, and the fleet sizing to determine, for instance, the mix of aircrafts to be hired for the next months or year (Hermeto et al., 2014; Belobaba et al., 2015).…”
Section: Introductionmentioning
confidence: 99%