The design of single allocation incomplete hub networks

Cataloged from PDF version of article.The hub location problem deals with finding the location of hub facilities and allocating the demand nodes to these hub facilities so as to effectively route the demand between any origin–destination pair. In the extensive literature on this challenging network design problem, it has widely been assumed that the subgraph induced by the hub nodes is complete. Relaxation of this basic assumption constitutes the starting point of the present work. In this study, we provide a uniform modeling treatment to all the single allocation variants of the existing hub location problems, under the incomplete hub network design. No network structure other than connectivity is imposed on the induced hub network. Within this context, the single allocation incomplete p-hub median, the incomplete hub location with fixed costs, the incomplete hub covering, and the incomplete p-hub center network design problems are defined, and efficient mathematical formulations for these problems with Oðn3Þ variables are introduced. Computational analyses with these formulations are presented on the various instances of the CAB data set and on the Turkish network. 2009 Elsevier Ltd. All rights reserved

INTEGRATED HUB LOCATION AND CAPACITATED VEHICLE ROUTING PROBLEM OVER INCOMPLETE HUB NETWORKS

Hub location problem is one of the most important topics encountered in transportation and logistics management. Along with the question of where to position hub facilities, how routes are determined is a further challenging problem. Although these two problems are often considered separately in the literature, here, in this study, the two are analyzed together. Firstly, we relax the restriction that a vehicle serves between each demand center and hub pair and propose a mixed-integer mathematical model for the single allocation p-hub median and capacitated vehicle routing problem with simultaneous pick-up and delivery. Moreover, while many studies in hub location problem literature assume that there is a complete hub network structure, we also relax this assumption and present the aforementioned model over incomplete hub networks. Computational analyses of the proposed models were conducted on various instances on the Turkish network. Results indicate that the different capacity levels of vehicles have an important impact on optimal hub locations, hub arc networks, and routing design

Bi-objective p-hub Location Problems

In this thesis, we introduce, model, and solve bi-objective hub location problems. The two well-known hub location problems from the literature, the p-hub median and p-hub center problems, are uni ed under a bi-objective setting considering the single, multiple, and r-allocation strategies. We developed a 3-index and a 4-index mixed-integer programming formulation for each of the allocation strategies. All the formulations are tested on the CAB dataset from the literature using a commercial optimization software. We observe the effect of different priorities given to the objectives on the locations of hub nodes, allocations, and the CPU time requirements with different allocation strategies under different values of problem parameters

The hub covering problem over incomplete hub networks

Cataloged from PDF version of article.The rising trend in the transportation and telecommunication systems increases the importance of hub location studies in recent years. Hubs are special types of facilities in many-to-many distribution systems where flows are consolidated and disseminated. Analogous to location models, p-hub median, p-hub center and hub covering problems have been studied in the literature. In this thesis, we focus on a special type of hub covering problem which we call as “Hub Covering Problem over Incomplete Hub Networks”. Most of the studies in the hub location literature assume that the hub nodes are fully interconnected. We observe that, especially in cargo delivery systems, hub network is not complete. Thus, in this study we relax this fundamental assumption and propose integer programming models for single and multi allocation cases of the hub covering problem. We also propose three heuristics for both single and multi allocation cases of the problem. During the computational performance of proposed models and heuristics, CAB data was used. Results and comparisons of these heuristics will also be discussed.Kalaycılar, MuratM.S

Hub location and Hub network design

Ankara : The Department of Industrial Engineering and the Institute of Engineering and Science of Bilkent University, 2009.Thesis (Ph.D.) -- Bilkent University, 2009.Includes bibliographical references leaves 138-150.he hub location problem deals with finding the location of hub facilities and allocating the demand nodes to these hub facilities so as to effectively route the demand between origin–destination pairs. Hub location problems arise in various application settings in telecommunication and transportation. In the extensive literature on the hub location problem, it has widely been assumed that the subgraph induced by the hub nodes is complete. Throughout this thesis we relax the complete hub network assumption in hub location problems and focus on designing hub networks that are not necessarily complete. We approach to hub location problems from a network design perspective. In addition to the location and allocation decisions, we also study the decision on how the hub network must be designed. We focus on the single allocation version of the problems where each demand center is allocated to a single hub node. We start with introducing the 3-stop hub covering network design problem. In this problem, we aim to design hub networks so that all origin– destination pairs receive service by visiting at most three hubs on a route. Then, we include hub network design decisions in the classical hub location problems introduced in the literature. We introduce the single allocation incomplete p-hub median, hub location with fixed costs, hub covering, and p-hub center network design problems to the literature. Lastly, we introduce the multimodal hub location and hub network design problem. We include the possibility of using different hub links, and allow for different transportation modes between hubs, and for different types of service time promises between origin–destination pairs, while designing the hub network in the multimodal problem. In this problem, we jointly consider transportation costs and travel times, which are studied separately in hub location problems presented in the literature. Computational analyses with all of the proposed models are presented on the various instances of the CAB data set and on the Turkish network.Alumur, Sibel AlevPh.D

Genetic algorithm-based optimization approach for an uncapacitated single allocation P-hub center problem with more realistic cost structure

Abstract A p-hub center network design problem consists of some nodes as hubs and allocation of non-hub nodes to them wherein the maximum travel times between any pair of nodes is minimized. The distinctive feature of this study is proposing a new mathematical formulation for modeling costs in a p-hub center problem. Here, instead of considering costs as a linear function of distance, for the first time, we formulate costs as a summation of different parts: fixed cost, health, safety and environment (HSE) cost, energy cost and personnel cost. Such integrated model results in a hard-tosolve nonlinear formulation. To validate the proposed model, a small scale problem instance of CAB dataset solved by LINGO software. We also prepared a Genetic Algorithm (GA) by MATLAB software to solve complete problems of CAB and AP datasets

Modeling and heuristic approaches for the Hub covering problem over incomplete Hub networks

Ankara : The Department of Industrial Engineering and the Institute of Engineering and Science of Bilkent University, 2009.Thesis (Master's) -- Bilkent University, 2009.Includes bibliographical references leaves 63-66.Hubs are the accumulation points within the transportation and the telecommunication networks that collect and distribute the flow or data, which is originated from a starting point and needs to be transferred to a destination point. The main application areas of the hub location problem are airline systems, telecommunication network design and cargo delivery systems. In the literature, a common treatment of hub location problems is under the classification dating back to the location literature. In this classification, four different types are identified. Namely, the p-hub median problem, the hub location problem with fixed costs, the p-hub center problem, and the hub covering problem in the literature. In most of the hub location studies, the hub networks are assumed to be complete; however, the observations on the real life cases showed that this may not be the case. Therefore, in this thesis, we relax this assumption and focus on the single allocation version of the hub covering problem over incomplete hub networks. We propose two new mathematical formulations and a tabu search based heuristic algorithm for this problem. We perform several computational experiments on the formulations with the CAB data set from the literature and a larger scale network corresponding to the cities in Turkey. The results we obtained from our experimentations reveals that designing incomplete hub networks to provide service within a given service time bound is cost effective in accordance with designing complete hub networks.Çalık, HaticeM.S

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