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This study is devoted to a new research topic in real-time airline operations, the redispatching of unit load devices (ULDs) under demand variations. We develop a new hybrid framework to solve the problem of ULD redispatch following the time-sequence decision-making required by airlines. The hybrid framework is developed by integrating techniques including the probability distribution technique to simulate different types of operational demand, the adjustable number of stages which is needed to meet the requirements of a decision-making process following a time sequence and the time pressure characteristic of real operations, and the scenario tree and probability rule approaches which are aimed and representing all possible demand scenarios for a stage, while the network flow technique is applied to represent the movement and location of ULDs at each airport over time and is used for the development of the associated mathematical model and the simulation. We performed a simulation of 2,000 cases based on different operational days and types of operational demand. The results show that this hybrid framework is able to achieve stability and also a small variability of both ULD operating costs and solution times, which could allow the airline to save on ULD operating costs, under demand variations in real-time operations. [ABSTRACT FROM AUTHOR]

In this paper, we develop an intercity bus scheduling model for a variable market share. The proposed model, unlike the past intercity bus scheduling models, does not assume a fixed market share. Instead, passenger choice behaviors in competitive markets are considered. The model is formulated as a nonlinear mixed integer program that is characterized as nondeterministic polynomial-time hard. We develop a solution algorithm to efficiently solve the model. The test results, which are based on a major Taiwan intercity bus carrier, show the good performance of the model and the solution algorithm. Index Terms--Intercity bus, nonlinear mixed integer program, scheduling, variable market shares.

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ejor.2006.05.002 Byline: Shangyao Yan, Ching-Hui Tang Keywords: Stochastic programming; Gate assignment; Stochastic flight delay; Real-time gate assignment Abstract: To make good flight to gate assignments, not only do all the relevant constraints have to be considered, but stochastic flight delays that occur in actual operations also have to be taken into account. In past research, airport gate assignments and stochastic disturbances have often been handled in the planning and the real-time stages separately, meaning that the interrelationship between these stages, as affected by such delays, has been neglected. In this research, we develop a heuristic approach embedded in a framework designed to help the airport authorities make airport gate assignments that are sensitive to stochastic flight delays. The framework includes three components, a stochastic gate assignment model, a real-time assignment rule, and two penalty adjustment methods. The test results are based on data supplied by a Taiwan international airport, and show that the proposed framework performs better than the current manual assignment process and the traditional deterministic model. Author Affiliation: Department of Civil Engineering, National Central University, Chungli 32054, Taiwan Article History: Received 21 June 2005; Accepted 3 May 2006

In this research, we develop a short-term flight scheduling model with variable market shares in order to help a Taiwan airline to solve for better fleet routes and flight schedules in today's competitive markets. The model is formulated as a nonlinear mixed integer program, characterized as an NP-hard problem, which is more difficult to solve than the traditional fixed market share flight scheduling problems, often formulated as integer/mixed integer linear programs. We develop a heuristic method to efficiently solve the model. The test results, mainly using the data from a major Taiwan airline's operations, show the good performance of the model and the solution algorithm. Keywords: Scheduling; Routing; Optimization; Variable market shares; Non-linear mixed integer program, 1. Introduction Fleet routing and flight scheduling are essential to a carrier's profitability, its level of service, its competitive capability, and its market share. There are many factors that need [...]

This paper addresses a competitive airline hub-and-spoke network design problem in a duopolistic market with sequential airline entry. Two airlines, a leader and a follower, enter the market sequentially to make decisions about their own flight networks. Each must consider their opponent's reactions and respond to each other's decisions in making their own, leading to interactive competition between them. A bi-level model is proposed to formulate the behaviors and decisions of the two airlines. In addition, an interactive solution procedure based on a genetic algorithm (GA) is developed to repeatedly solve the upper and lower level models. Finally, we generate a numerical example based on the regional air market in Taiwan and China. The results provide useful insights and highlight the importance of considering interactive competition for airlines when designing their flight networks. [ABSTRACT FROM AUTHOR]

This study considers the planned gate and runway assignment problem for minimizing carbon emissions and costs during the aircraft taxiing stage. The distances between multiple gates and runways, the fuel consumption of different types of aircraft, the location of terminal buildings belonging to the airline, the size of parking aprons for aircraft, and runway lengths for different types of aircraft are all considered. We propose the following two objectives: the minimization of carbon emissions and the minimization of carbon emission costs for airport and for airlines, respectively. A case study based on operations of Taiwan's Taoyuan International Airport is performed. Analytical results indicate that our assignments can achieve an 8.93% reduction of carbon emissions and 10.33% reduction of carbon emission costs compared with the current assignments. [ABSTRACT FROM AUTHOR]

In this research, we consider a flight scheduling problem for oligopolistic competition with direct flights and a point to point network. In this type of market situation, passengers are sensitive to the departure time of a flight rather than the transfer time. The airline needs to carefully consider the departure times of their competitors when determining their own. Therefore, unlike past approaches which have only considered one departure time for a competitor's flight, a flight scheduling framework is developed which takes into consideration possible competitor departure times. The framework includes two dependent stages which are repeatedly solved during the solution process. In addition, an upper bound model is also designed to evaluate the solution quality. Numerical tests are performed using data for Taiwan's outlying island route which is characterized by the above market situation. Satisfactory results are obtained, showing the good performance of the framework. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY This work presents an analysis of the fleet size determination problem for a truckload distribution center in which each customer requests multi-truckload services. A transformation is made to define this problem as a cutting stock problem which can be resolved by finding the proper set of patterns beneficial for an NP-hard (non-deterministic polynomial-time hard) problem. The genetic algorithm (GA) is combined with cutting stock techniques to solve the problem. Experiments are carried out testing two types of problems, with and without time-window constraints. To verify the solution quality obtained with the proposed approach, the problem is also solved using only GA. It is shown that the proposed approach can significantly improve the GA solution by 14.68%. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY It is often the case in actual airport operations that flight departure/arrival information will vary with time. In practice, flight departure/arrival times closer to the time when the airport authority starts to plan the reassignments tend to be more certain; those further away tend to be more stochastic. These two types of flights can be called deterministic flights and stochastic flights, respectively. A deterministic flight has a certain departure/arrival time; while a stochastic flight will have a variety of stochastic departure/arrival times. In this study the aim is to develop a gate reassignment model (GRM) designed to consider both deterministic and stochastic flight departure/arrival times. A 0-1 integer programming technique is applied to formulate the GRM. In practice gate reassignments need to be handled repeatedly, so to make this possible the GRM is applied to a dynamic gate reassignment framework (DGRF). The theoretical effectiveness of the GRM applied to the DGRF is evaluated by the development of a lower bound solution. Numerical tests, related to the operations of an international Taiwan airport, show that the proposed GRM and DGRF perform well. Copyright © 2010 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Temporary gate shortages and stochastic flight delays (including late departures or arrivals and early arrivals) are common problems that often occur simultaneously in real-time airport operations. The aim of this paper is to design a gate reassignment model to deal with temporary gate shortages and stochastic flight delays. This is done by allowing the violation of gate reassignment constraints in the model. A numerical test was carried out, based on data from the operations of the Taiwan Taoyuan Airport (a major international airport in Taiwan), to demonstrate the performance of the proposed model. A comparison of the proposed model and a traditional reassignment model, as well as major findings related to the test results, are also discussed and presented. [ABSTRACT FROM AUTHOR]