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

Routing and scheduling decisions in the hierarchical hub location problem

Hubs are facilities that consolidate and disseminate flow in many-to-many distribution systems. The hub location problem considers decisions that include the locations of hubs in a network and the allocations of demand (non-hub) nodes to these hubs. We propose a hierarchical multimodal hub network structure, and based on this network, we define a hub covering problem with a service time bound. The hierarchical network consists of three layers in which we consider a ring-star-star (RSS) network. This multimodal network may have different types of vehicles in each layer. For the proposed problem, we present and strengthen a mathematical model with some variable fixing rules and valid inequalities. Also, we develop a heuristic solution algorithm based on the subgradient approach to solve the problem in more reasonable times. We conduct the computational analysis over the Turkish network and the CAB data sets. © 2017 Elsevier Lt

Routing and scheduling decisions in the hierarchical hub location problem

Hubs are facilities that consolidate and disseminate flow in many-to-many distribution systems. The hub location problem considers decisions that include the locations of hubs in a network and also the allocations of the demand (non-hub) nodes to these hubs. We propose a hierarchical multimodal hub network. Based on this network, we define a hub covering problem with a service time bound. The hierarchical network consists of three layers. We consider two different structures: ring-star-star (RSS) and ring-ring-star (RRS). The multimodal network has three different types of vehicles in each layer: airplanes, large trucks and small trucks. For the proposed problems (RSS and RRS), we present and strengthen two mathematical models with some variable fixing rules and valid inequalities. We conduct the computational analysis over the Turkish network and the CAB data sets

Enriching the tactical network design of express service carriers with fleet scheduling characteristics

Express service carriers provide time-guaranteed deliveries of parcels via a network consisting of nodes and hubs. In this, nodes take care of the collection and delivery of parcels, and hubs have the function to consolidate parcels in between the nodes. The tactical network design problem assigns nodes to hubs, determines arcs between hubs, and routes parcels through the network. Afterwards, fleet scheduling creates a schedule for vehicles operated in the network. The strong relation between flow routing and fleet scheduling makes it difficult to optimise the network cost. Due to this complexity, fleet scheduling and network design are usually decoupled. We propose a new tactical network design model that is able to include fleet scheduling characteristics (like vehicle capacities, vehicle balancing, and drivers' legislations) in the network design. The model is tested on benchmark data based on instances from an express provider, resulting in significant cost reductions

Random Sequential Renormalization of Networks I: Application to Critical Trees

We introduce the concept of Random Sequential Renormalization (RSR) for arbitrary networks. RSR is a graph renormalization procedure that locally aggregates nodes to produce a coarse grained network. It is analogous to the (quasi-)parallel renormalization schemes introduced by C. Song {\it et al.} (Nature {\bf 433}, 392 (2005)) and studied more recently by F. Radicchi {\it et al.} (Phys. Rev. Lett. {\bf 101}, 148701 (2008)), but much simpler and easier to implement. In this first paper we apply RSR to critical trees and derive analytical results consistent with numerical simulations. Critical trees exhibit three regimes in their evolution under RSR: (i) An initial regime $N_0^{\nu}\lesssim N<N_0$, where $N$ is the number of nodes at some step in the renormalization and $N_0$ is the initial size. RSR in this regime is described by a mean field theory and fluctuations from one realization to another are small. The exponent $\nu=1/2$ is derived using random walk arguments. The degree distribution becomes broader under successive renormalization -- reaching a power law, $p_k\sim 1/k^{\gamma}$ with $\gamma=2$ and a variance that diverges as $N_0^{1/2}$ at the end of this regime. Both of these results are derived based on a scaling theory. (ii) An intermediate regime for $N_0^{1/4}\lesssim N \lesssim N_0^{1/2}$, in which hubs develop, and fluctuations between different realizations of the RSR are large. Crossover functions exhibiting finite size scaling, in the critical region $N\sim N_0^{1/2} \to \infty$, connect the behaviors in the first two regimes. (iii) The last regime, for $1 \ll N\lesssim N_0^{1/4}$, is characterized by the appearance of star configurations with a central hub surrounded by many leaves. The distribution of sizes where stars first form is found numerically to be a power law up to a cutoff that scales as $N_0^{\nu_{star}}$ with $\nu_{star}\approx 1/4$

Design and optimization of fuel injection of a 50 kW micro turbogas

The present article deals with the design of a micro turbogas turbine suitable for on board applications, e.g., as a power generator on hybrid transit bus, characterized by a simple constructive approach. Deriving the machine layout from an existing KJ-66 aircraft model engine, the authors propose a theoretical design of a compact, lightweight turbogas turbine, by investigating the technical possibility and limits of the proposed design. In particular, a different combustion chamber layout has been proposed, and fuel adduction channels for different swirler designs have been simulated via ANSYS Fluent in order to identify a satisfactory fuel spreading. As a result, the complete characterization of the design parameters and geometries has been performed, and a series of RANS simulations has been used in order to identify an optimal swirler configuration

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

Horizontal visibility graphs transformed from fractional Brownian motions: Topological properties versus Hurst index

Nonlinear time series analysis aims at understanding the dynamics of stochastic or chaotic processes. In recent years, quite a few methods have been proposed to transform a single time series to a complex network so that the dynamics of the process can be understood by investigating the topological properties of the network. We study the topological properties of horizontal visibility graphs constructed from fractional Brownian motions with different Hurst index $H\in(0,1)$. Special attention has been paid to the impact of Hurst index on the topological properties. It is found that the clustering coefficient $C$ decreases when $H$ increases. We also found that the mean length $L$ of the shortest paths increases exponentially with $H$ for fixed length $N$ of the original time series. In addition, $L$ increases linearly with respect to $N$ when $H$ is close to 1 and in a logarithmic form when $H$ is close to 0. Although the occurrence of different motifs changes with $H$, the motif rank pattern remains unchanged for different $H$. Adopting the node-covering box-counting method, the horizontal visibility graphs are found to be fractals and the fractal dimension $d_B$ decreases with $H$. Furthermore, the Pearson coefficients of the networks are positive and the degree-degree correlations increase with the degree, which indicate that the horizontal visibility graphs are assortative. With the increase of $H$, the Pearson coefficient decreases first and then increases, in which the turning point is around $H=0.6$. The presence of both fractality and assortativity in the horizontal visibility graphs converted from fractional Brownian motions is different from many cases where fractal networks are usually disassortative.Comment: 12 pages, 8 figure