TY - JOUR
T1 - Airline planning benchmark problems—Part II
T2 - passenger groups, utility and demand allocation
AU - Akartunali, Kerem
AU - Boland, Natashia
AU - Evans, Ian
AU - Wallace, Mark
AU - Waterer, Hamish
PY - 2013/3
Y1 - 2013/3
N2 - This paper is the second of two papers entitled “Airline Planning Benchmark Problems”, aimed at developing benchmark data that can be used to stimulate innovation in airline planning, in particular, in flight schedule design and fleet assignment. The former has, to date, been under-represented in the optimisation literature, due in part to the difficulty of obtaining data that adequately reflects passenger choice, and hence schedule revenue. Revenue models in airline planning optimisation only roughly approximate the passenger decision process. However, there is a growing body of literature giving empirical insights into airline passenger choice. Here we propose a new paradigm for passenger modelling, that enriches our representation of passenger revenue, in a form designed to be useful for optimisation. We divide the market demand into market segments, or passenger groups, according to characteristics that differentiate behaviour in terms of airline product selection. Each passenger group has an origin, destination, size (number of passengers), departure time window, and departure time utility curve, indicating willingness to pay for departure in time sub-windows. Taking as input market demand for each origin–destination pair, we describe a process by which we construct realistic passenger group data, based on the analysis of empirical airline data collected by our industry partner. We give the results of that analysis, and describe 33 benchmark instances produced.
AB - This paper is the second of two papers entitled “Airline Planning Benchmark Problems”, aimed at developing benchmark data that can be used to stimulate innovation in airline planning, in particular, in flight schedule design and fleet assignment. The former has, to date, been under-represented in the optimisation literature, due in part to the difficulty of obtaining data that adequately reflects passenger choice, and hence schedule revenue. Revenue models in airline planning optimisation only roughly approximate the passenger decision process. However, there is a growing body of literature giving empirical insights into airline passenger choice. Here we propose a new paradigm for passenger modelling, that enriches our representation of passenger revenue, in a form designed to be useful for optimisation. We divide the market demand into market segments, or passenger groups, according to characteristics that differentiate behaviour in terms of airline product selection. Each passenger group has an origin, destination, size (number of passengers), departure time window, and departure time utility curve, indicating willingness to pay for departure in time sub-windows. Taking as input market demand for each origin–destination pair, we describe a process by which we construct realistic passenger group data, based on the analysis of empirical airline data collected by our industry partner. We give the results of that analysis, and describe 33 benchmark instances produced.
KW - airline planning
KW - passenger choice models
KW - revenue models
KW - benchmark data
UR - http://www.scopus.com/inward/record.url?scp=84870247143&partnerID=8YFLogxK
U2 - 10.1016/j.cor.2012.03.005
DO - 10.1016/j.cor.2012.03.005
M3 - Article
SN - 0305-0548
VL - 40
SP - 793
EP - 804
JO - Computers & Operations Research
JF - Computers & Operations Research
IS - 3
ER -