A Combined Average-Case and Worst-Case Analysis for an Integrated Hub Location and Revenue Management Problem

Abstract

This paper investigates joint decisions on airline network design and capacity allocation by integrating an uncapacitated single allocation p-hub median location problem into a revenue management problem. For the situation in which uncertain demand can be captured by a finite set of scenarios, we extend this integrated problem with average profit maximization to a combined average-case and worst-case analysis of this integration. We formulate this problem as a two-stage stochastic programming framework to maximize the profit, including the cost of installing the hubs and a weighted sum of average and worst case transportation cost and the revenue from tickets over all scenarios. This model can give flexible decisions by putting the emphasis on the importance of average and worst case profits. To solve this problem, a genetic algorithm is applied. Computational results demonstrate the outperformance of the proposed formulation.

EFP‐GA: An Extended Fuzzy Programming Model and a Genetic Algorithm for Management of the Integrated Hub Location and Revenue Model under Uncertainty

“…In another category, it is derived from a combination of pricing and hub location [10]. Finally, integrated revenue management and hub location are considered another category [11,12]. Hörhammer [13] studied a dynamic multiperiod hub location problem with multiple capacity levels.…”

“…A robust integrated optimization and stochastic programming to maximize weighted total profit is presented to obtain reasonable solutions. Huo et al [11] studied an integrated hub location and revenue management problem considering average and worst-case analysis. A p-hub is selected from n nodes while uncertain data and some scenarios are considered in the study.…”

“…Equation (10) ensures that each nonhub node should be allocated to only one hub. Equation (11) states that there are precisely p-hubs in the network. Equation (12) enforces that a nonhub node has been allocated to a hub node if this node had been selected as a hub.…”

Emergency Strategies of Closed-Loop Supply Chain with Single Retailer Recycling under Demand Disruptions

“…By substituting the upper values into q * > q * and τ * < τ * , it can be obtained that φ ≤ (1 − β)λ 1 and φ > (1 − β)λ 1 . As we cannot get a feasible solution, the conclusion is drawn that the scenario (1) has no solution when c � 0. To sum up, we can get the range of demand disruption in Scenario Ι as 0 < φ < (1 − β)λ 1 .…”

“…Actually, enterprises participating in CLSC operation can not only win the market share and considerable profits but also have a good impact on the whole ecological environment [1][2][3][4]. For instance, Xerox Corporation provides prepaid mailboxes so that customers can easily return their used copy or print cartridges to Xerox without any costs [5].…”