Comparison of the formulations for a hub-and-spoke network design problem under congestion

In this paper, we study the hub location problem with a power-law congestion cost and propose an exact solution approach. We formulate this problem in a conic quadratic form and use a strengthening method which rests on valid inequalities of perspective cuts in mixed integer nonlinear programming. In a numerical study, we compare two well known types of mathematical modeling in the hub-location problems which are solved with different branch and cut strategies. The strength and weakness of the formulations are summarized based on an extensive numerical study over the CAB data set

Solving the Uncapacitated Single Allocation p-Hub Median Problem on GPU

A parallel genetic algorithm (GA) implemented on GPU clusters is proposed to solve the Uncapacitated Single Allocation p-Hub Median problem. The GA uses binary and integer encoding and genetic operators adapted to this problem. Our GA is improved by generated initial solution with hubs located at middle nodes. The obtained experimental results are compared with the best known solutions on all benchmarks on instances up to 1000 nodes. Furthermore, we solve our own randomly generated instances up to 6000 nodes. Our approach outperforms most well-known heuristics in terms of solution quality and time execution and it allows hitherto unsolved problems to be solved

Air Taxi Skyport Location Problem for Airport Access

Witnessing the rapid progress and accelerated commercialization made in recent years for the introduction of air taxi services in near future across metropolitan cities, our research focuses on one of the most important consideration for such services, i.e., infrastructure planning (also known as skyports). We consider design of skyport locations for air taxis accessing airports, where we present the skyport location problem as a modified single-allocation p-hub median location problem integrating choice-constrained user mode choice behavior into the decision process. Our approach focuses on two alternative objectives i.e., maximizing air taxi ridership and maximizing air taxi revenue. The proposed models in the study incorporate trade-offs between trip length and trip cost based on mode choice behavior of travelers to determine optimal choices of skyports in an urban city. We examine the sensitivity of skyport locations based on two objectives, three air taxi pricing strategies, and varying transfer times at skyports. A case study of New York City is conducted considering a network of 149 taxi zones and 3 airports with over 20 million for-hire-vehicles trip data to the airports to discuss insights around the choice of skyport locations in the city, and demand allocation to different skyports under various parameter settings. Results suggest that a minimum of 9 skyports located between Manhattan, Queens and Brooklyn can adequately accommodate the airport access travel needs and are sufficiently stable against transfer time increases. Findings from this study can help air taxi providers strategize infrastructure design options and investment decisions based on skyport location choices.Comment: 25 page

Network hub locations problems: the state of the art

Cataloged from PDF version of article.Hubs are special facilities that serve as switching, transshipment and sorting points in many-to-many distribution systems. The hub location problem is concerned with locating hub facilities and allocating demand nodes to hubs in order to route the traffic between origin-destination pairs. In this paper we classify and survey network hub location models. We also include some recent trends on hub location and provide a synthesis of the literature. (C) 2007 Elsevier B.V. All rights reserved

Applications of Game Theory for Co-opetition at Marine Container Terminals

Applications of Game Theory for Co-opetition at Marine Container Terminal

Optimal CH-47 and C-130 Workload Balance

The Air Force can save thousands of dollars by reducing the number of blade hours on the CH-47 through finding an optimal mixture of CH-47s and C-130s to conduct current operations in Afghanistan and Iraq. Ultimately these savings will relieve maintenance operations for the CH-47 and lengthen the lifespan of the CH-47 airframe. Moreover, incorporating C-130s into the operations will reduce cargo transit time from supply depots. This study looks at the involvement of the C-130 in CH-47 airlift operations to reduce CH-47 usage and increase supply efficiency. The research focus is narrowed to current airlift operations in Afghanistan and Iraq in the CENTCOM theater of operation. A mathematical representation of current CH-47 operations augmented with C-130s is the foundation of this research. Particularly, these operations in CENTCOM\u27s area of operations are formulated as linear transportation problems using network mathematics. The uniqueness this research offers entails modified scenarios of the transportation problem solved as an optimization model. AMC requires additional constraints to be augmented with the basic transportation linear model that pushes this application in new areas. In addition, the uncommon layout of supply depots to the specified receiving airfields in Afghanistan and Iraq provide an altogether new kind of transportation problem

Evaluating the Vulnerability of Time-Sensitive Transportation Networks: A Hub Center Interdiction Problem

This work is licensed under a Creative Commons Attribution 4.0 International License.Time-sensitive transportation systems have received increasing research attention recently. Examples of time-sensitive networks include those of perishable goods, high-value commodity, and express delivery. Much research has been devoted to optimally locating key facilities such as transportation hubs to minimize transit time. However, there is a lack of research attention to the reliability and vulnerability of time-sensitive transportation networks. Such issues cannot be ignored as facilities can be lost due to reasons such as extreme weather, equipment malfunction, and even intentional attacks. This paper proposes a hub interdiction center (HIC) model for evaluating the vulnerability of time-sensitive hub-and-spoke networks under disruptions. The model identifies the set of hub facilities whose loss will lead to the greatest increase in the worst-case transit time. From a planning perspective, such hubs are critical facilities that should be protected or enhanced by preventive measures. An efficient integer linear programming (ILP) formulation of the new model is developed. Computational experiments on a widely used US air passenger dataset show that losing a small number of hub facilities can double the maximum transit time

Optimization of Hybrid Hub-and-Spoke Network Operation for Less-Than-Truckload Freight Transportation considering Incremental Quantity Discount

This paper presents a mixed integer linear programming model (MILP) for optimizing the hybrid hub-and-spoke network operation for a less-than-truckload transportation service. The model aims to minimize the total operation costs (transportation cost and transfer cost), given the determined demand matrix, truck load capacity, and uncapacitated road transportation. The model also incorporates an incremental quantity discount function to solve the reversal of the total cost and the total demand. The model is applied to a real case of a Chinese transportation company engaged in nationwide freight transportation. The numerical example shows that, with uncapacitated road transportation, the total costs and the total vehicle trips of the hybrid hub-and-spoke network operation are, respectively, 8.0% and 15.3% less than those of the pure hub-and-spoke network operation, and the assumed capacity constraints in an extension model result in more target costs on the hybrid hub-and-spoke network. The two models can be used to support the decision making in network operations by transportation and logistics companies

Collaborative rescheduling of flights in a single mega-hub network

Traditionally, airlines have configured flight operations into a Hub and Spoke network design. Using connecting arrival departure waves at multiple hubs these networks achieve efficient passenger flows. Recently, there has been much growth in the development of global single mega-hub (SMH) flight networks that have a significantly different operating cost structure and schedule design. These are located primarily in the Middle East and are commonly referred to as the ME3. The traditionalist view is that SMH networks are money losers and subsidized by sovereign funds. This research studies and analyzes SMH networks in an attempt to better understand their flight efficiency drivers. Key characteristics of SMH airports are identified as: (i) There are no peak periods, and flight activity is balanced with coordinated waves (ii) No priority is assigned to arrival/departure times at destinations (selfish strategy) only hub connectivity is considered (iii) There is less than 5% OD traffic at SMH (iv) The airline operates only non-stop flights (v) Passengers accept longer travel times in exchange for economic benefits (vi) Airline and airport owners work together to achieve collaborative flight schedules. This research focuses on the network structure of SMH airports to identify and optimize the operational characteristics that are the source of their advantages. A key feature of SMH airports is that the airline and airport are closely aligned in a partnership. To model this relationship, the Mega-Hub Collaborative Flight Rescheduling (MCFR). Problem is introduced. The MCFR starts with an initial flight schedule developed by the airline, then formulates a cooperative objective which is optimized iteratively by a series of reschedules. Specifically, in a network of iEM cities, the decision variables are i* the flight to be rescheduled, Di* the new departure time of flight to city i* and Hi* the new hold time at the destinatioin city i*. The daily passenger traffic is given by Ni,j and normally distributed with parameters µNi,j and sNi,j. A three-term MCFR objective function is developed to represent the intersecting scheduling decision space between airlines and airports: (i) Passenger Waiting Time (ii) Passenger Volume in Terminal, and (iii) Ground Activity Wave Imbalance. The function is non-linear in nature and the associated constraints and definitions are also non-linear. An EXCEL/VBA based simulator is developed to simulate the passenger traffic flows and generate the expected cost objective for a given flight network. This simulator is able to handle up to an M=250 flight network tracking 6250 passenger arcs. A simulation optimization approach is used to solve the MCFR. A Wave Gain Loss (WGL) strategy estimates the impact Zi of flight shift Δi on the objective. The WGL iteratively reschedules flights and is formulated as a non-linear program. It includes functions to capture the traffic affinity driven solution dependency between flights, the relationship between passengers in terminal gradients and flight shifts, and the relationship between ground traffic activity gradients and flight shifts. Each iteration generates a Zi ranked list of flights. The WGL is integrated with the EXCEL/VBA simulator and shown to generate significant costs reduction in an efficient time. Extensive testing is done on a set of 5 flight network problems, each with 3 different passengers flow networks characterized by low, medium and high traffic concentrations