Search

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]

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]