A Memetic Algorithm for Designing a Capacitated Hub Network under Demand Uncertainty and Disruption

Abstract

<span style="font-family: 'Times New Roman','serif'; font-size: 11pt; mso-fareast-font-family: 'Times New Roman'; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: FA;">Hub location problems are among the extensions of<br />classical location problems that have numerous applications in designing<br />transportation, postal, and telecommunication networks. Despite the evident<br />attention of researchers to these problems, there are few studies on designing<br />hub networks under uncertainty and disruption. In this study, the capacitated<br />single allocation hub location problem under demand uncertainty and disruption<br />is investigated. First, a mathematical model based on budget of uncertainty<br />concept is proposed, then a hybrid solution method based on genetic algorithm<br />and variable neighborhood search is proposed. Computational experiments<br />demonstrate the accuracy of the proposed solution method in solving the test<br />instances. In addition, the results obtained from conducting Monte-Carlo<br />simulation experiments to analyze the effects of uncertainty on the performance<br />of different hub network configurations show the necessity of considering<br />demand uncertainty and disruption while designing hub networks.</span>