Milica Kalić

The potential for using fuzzy set theory in airline network design

This paper develops a model to design an airline network and determine flight frequencies. The basic input data are the estimated numbers of passengers between pairs of cities. It is often impossible to estimate these numbers with enough precision (i.e. there is a degree of uncertainty surrounding the numbers of passengers between pairs of cities). Uncertainty is also frequent in the estimation of future airline carrier costs. The fuzzy set theory is an extremely convenient mathematical device with which to solve problems containing uncertainty, sujectivity, ambiguity and indetermination. Without aspiring to revolutionize airline netqork design, the basic goal of this paper is to present the fuzzy set tools and their potential application to a generic airline network design problem. The model developed is based on the fuzzy set theory. The first part of the model uses fuzzy logic to determine the route candidates to make the flights, and the second part of the model is based on fuzzy linear programming to determine flight frequencies on the route candidates. The model is supported by numerical examples.

A Fuzzy route choice model for air transportation networks

The paper develops a route choice model for air transportation networks. Since the route choice process is characterized by uncertainty and subjectivity, the model is based on Fuzzy Set Theory, which utilises the principles of fuzzy logic. The approximate reasoning model developed is tested using real data. Excellent correspondence was achieved between the results obtained from using the model and the real data.

TRIP DISTRIBUTION MODELLING USING FUZZY LOGIC AND A GENETIC ALGORITHM

This article examines possibilities for the application of soft computing techniques for the prediction of travel demand. The model, based on fuzzy logic and a genetic algorithm, successfully solves the trip distribution problem. The possibilities of using the proposed model in solving trip generation, modal split and route choice problems have also been indicated. The model has been tested on a real numerical example. Exceptionally good correspondences between estimated and real values of passenger flows have been obtained.

Air Travel Demand Fuzzy Modelling: Trip Generation and Trip Distribution

This chapter describes the fuzzy logic approach to modelling of trip generation and trip distribution on country and country-pair levels. Different economic (GDP per capita of origin country, imports by destination countries) and social factors, as well as other ones (number of emigrants in destination country and destination country attractiveness) are considered. The case study of Serbia, illustrating possibilities of models, is given. Results of this research provide empirical evidence relating to successful use of fuzzy logic as a non-traditional technique.

The Fuzzy System Sensitivity Analysis: An Example of Air Travel Demand Models

This chapter presents the results obtained by employing both fuzzy logic and sensitivity analysis to model trip generation and trip distribution processes in the domain of air transportation. Qualitative and imprecise information taken from experts represent an invaluable source when objective knowledge on certain process is not available or even does not exist. Thus, fuzzy logic is seen as a convenient mathematical tool that efficiently treats uncertainty in-built in the socio-economic parameters that are selected to describe trip generation and trip distribution problem. The chapter analyzes the sensitivity of fuzzy system solutions obtained by two models in respect to different factors such as domain discretization of input and output variables, various forms of membership function and different approximate reasoning techniques hereby enabling possible improvements to the models.

Airline efficiency performance in the turbulent period before and after economic crisis

JOVANA G. KULJANIN, University of Belgrade, Professional paper Faculty of Transport and Traffic Engineering, Belgrade UDC: 005.51/.52:656.7 MILICA Đ. KALIĆ, University of Belgrade, 339.13.017:656.7 Faculty of Transport and Traffic Engineering, Belgrade DOI: 10.5937/tehnika1705725K LEONARDO G. CAGGIANI, Polytechnic University of Bari, Bari, Italy MICHELE G. OTTOMANELLI, Polytechnic University of Bari, Bari, Italy

Aircraft Type Selection Problem: Application of Different MCDM Methods

In order to make a proper choice when selecting aircraft type, planners can apply some of multiple criteria decision-making (MCDM) methods as an aid to decision making. In this paper, three MCDM methods, Analytic Hierarchy Process (AHP) and Fuzzy Analytic Hierarchy Process (FAHP) as widely used methods based on hierarchy and Even Swaps Method (ESM) that belongs to group of so-called dominance methods, are applied onto the same problem, under the same conditions and illustrated with a case study of a hypothetical airline. These methods are compared, as well as solutions they arrived at. Considering the difference among the methods, a sensitivity analysis is carried out in different ways. In the AHP and FAHP, the sensitivity of alternative ratings in respect to different pairwise comparisons of the alternatives is analyzed, showing that the methods are sensitive to this kind of changing. In the even swaps method, the objective ranking across alternatives is varied, showing that the ESM is not sensitive at all.

Airline network structure in competitive market

Airlines network is the key element of its business strategy and selected network structure will not have influence only on the airlines costs but could gain some advantage in revenues, too. Network designing implies that an airline has to make decisions about markets that it will serve and how to serve those markets. Network choice raises the following questions for an airline: a) what markets to serve, b) how to serve selected markets, c) what level of service to offer, d) what are the benefits/cost of the that decisions and e) what is the influence of the competition. We analyzed the existing airline business models and corresponding network structure. The paper highlights the relationship between the network structures and the airline business strategies. Using a simple model we examine the relationship between the network structure and service quality in deregulated market.