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

Jia-Zhen Huo,Jun-Kai He,Yan-Ting Hou,Feng Chu

doi:10.1155/2019/8651728

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.

Highlights

Since the airline deregulation act enacted in 1978, airlines introduce the concept of revenue management, restructure airline network and develop centralized airline control centers to establish and sustain a competitive edge in this marketdriven environment [1]
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
Our aim is to maximize the profit of integrating a hub location problem into a revenue management problem and to provide less conservative and restrictive solutions by a weight-based combination of average-case and worst-case profits

Summary

Introduction

Since the airline deregulation act enacted in 1978, airlines introduce the concept of revenue management, restructure airline network and develop centralized airline control centers to establish and sustain a competitive edge in this marketdriven environment [1]. In the area of revenue management, the flows can be performed as air tickets which can be effectively allocated to different segments of customers to obtain more revenue. Our research is inspired by a weight-based combined consideration of the average-case and worst-case values in [4] They provide a flexible decision for an emergency response network design problem by putting relative emphasis on average-case and worst-case cost. Our aim is to maximize the profit of integrating a hub location problem into a revenue management problem and to provide less conservative and restrictive solutions by a weight-based combination of average-case and worst-case profits

Objectives

Results

Conclusion