336 research outputs found
A spanning tree approach to the absolute p-center problem
Cataloged from PDF version of article.We consider the absolute p-center problem on a general network and propose a spanning tree approach which is motivated by the fact that the problem is NP-hard on general networks but solvable in polynomial time on trees. We first prove that every connected network possesses a spanning tree whose p-center solution is also a solution for the network under consideration. Then we propose two classes of spanning trees that are shortest path trees rooted at certain points of the network. We give an experimental study, based on 1440 instances, to test how often these classes of trees include an optimizing tree. We report our computational results on the performance of both types of trees. © 1999 Elsevier Science Ltd. All rights reserved
New formulations of the Hop-Constrained Minimum Spanning Tree problem via Miller–Tucker–Zemlin constraints
Cataloged from PDF version of article.Given an undirected network with positive edge costs and a natural number p, the Hop-Constrained Minimum
Spanning Tree problem (HMST) is the problem of finding a spanning tree with minimum total cost
such that each path starting from a specified root node has no more than p hops (edges). In this paper, we
develop new formulations for HMST. The formulations are based on Miller–Tucker–Zemlin (MTZ) subtour
elimination constraints, MTZ-based liftings in the literature offered for HMST, and a new set of topologyenforcing
constraints. We also compare the proposed models with the MTZ-based models in the literature
with respect to linear programming relaxation bounds and solution times. The results indicate that
the new models give considerably better bounds and solution times than their counterparts in the literature
and that the new set of constraints is competitive with liftings to MTZ constraints, some of which
are based on well-known, strong liftings of Desrochers and Laporte (1991).
2011 Elsevier B.V. All rights reserved
Optimization of transportation requirements in the deployment of military units
Cataloged from PDF version of article.We study the deployment planning problem (DPP) that may roughly be defined as the problem of the planning of
the physical movement of military units, stationed at geographically dispersed locations, from their home bases to
their designated destinations while obeying constraints on scheduling and routing issues as well as on the availability
and use of various types of transportation assets that operate on a multimodal transportation network. The DPP is a
large-scale real-world problem for which analytical models do not exist.We propose a model for solving the problem
and develop a solution methodology which involves an effective use of relaxation and restriction that significantly
speeds up a CPLEX-based branch-and-bound. The solution times for intermediate-sized problems are around 1 h
at maximum, whereas it takes about a week in the Turkish Armed Forces to produce a suboptimal feasible solution
based on trial-and-error methods. The proposed model can be used to evaluate and assess investment decisions
in transportation infrastructure and transportation assets as well as to plan and execute cost-effective deployment
operations at different levels of planning.
2005 Elsevier Ltd. All rights reserved
On the single assignment p-Hub center problem
Cataloged from PDF version of article.We study the computational aspects of the single-assignment p-hub center problem on the basis of a basic model and a new model. The new model's performance is substantially better in CPU time than different linearizations of the basic model. We also prove the NP-Hardness of the problem. (C) 2000 Elsevier Science B.V. All rights reserved
The latest arrival hub location problem for cargo delivery systems with stopovers
Cataloged from PDF version of article.In this paper, we concentrate on the service structure of ground-transportation based cargo delivery companies. The
transient times that arise from nonsimultaneous arrivals at hubs (typically spent for unloading, loading, and sorting operations)
can constitute a significant portion of the total delivery time for cargo delivery systems. The latest arrival hub location
problem is a new minimax model that focuses on the minimization of the arrival time of the last item to arrive, taking
into account journey times as well as the transient times at hubs. We first focus on a typical cargo delivery firm operating in
Turkey and observe that stopovers are essential components of a ground-based cargo delivery system. The existing formulations
of the hub location problem in the literature do not allow stopovers since they assume direct connections between
demand centers and hubs. In this paper, we propose a generic mathematical model, which allows stopovers for the latest
arrival hub location problem. We improve the model using valid inequalities and lifting. We present computational results
using data from the US and Turkey.
2007 Elsevier Ltd. All rights reserved
Compromising system and user interests in shelter location and evacuation planning
Cataloged from PDF version of article.Traffic management during an evacuation and the decision of where to locate the shelters
are of critical importance to the performance of an evacuation plan. From the evacuation
management authority’s point of view, the desirable goal is to minimize the total evacuation
time by computing a system optimum (SO). However, evacuees may not be willing to
take long routes enforced on them by a SO solution; but they may consent to taking routes
with lengths not longer than the shortest path to the nearest shelter site by more than a
tolerable factor. We develop a model that optimally locates shelters and assigns evacuees
to the nearest shelter sites by assigning them to shortest paths, shortest and nearest with a
given degree of tolerance, so that the total evacuation time is minimized. As the travel time
on a road segment is often modeled as a nonlinear function of the flow on the segment, the
resulting model is a nonlinear mixed integer programming model. We develop a solution
method that can handle practical size problems using second order cone programming
techniques. Using our model, we investigate the importance of the number and locations
of shelter sites and the trade-off between efficiency and fairness.
2014 Elsevier Ltd. All rights reserved
A spanning tree approach to the absolute p-center problem
We consider the absolute p-center problem on a general network and propose a spanning tree approach which is motivated by the fact that the problem is NP-hard on general networks but solvable in polynomial time on trees. We first prove that every connected network possesses a spanning tree whose p-center solution is also a solution for the network under consideration. Then we propose two classes of spanning trees that are shortest path trees rooted at certain points of the network. We give an experimental study, based on 1440 instances, to test how often these classes of trees include an optimizing tree. We report our computational results on the performance of both types of trees. © 1999 Elsevier Science Ltd. All rights reserved
Introduction: revolution and counter-revolution in Egypt
This introduction to the ROAPE debate reasserts the centrality of revolutionary theory
to understand the dynamics of social and political struggles in contemporary Middle East and
North Africa. Framed around the conceptual and political interventions brought about by Brecht
De Smet’s Gramsci on Tahrir (2016), we discuss the utility of Gramscian concepts in explaining the
trajectories of social mobilisations in the peripheries of global capitalism
Risk based facility location by using fault tree analysis in disaster management
Determining the locations of facilities for prepositioning supplies to be used during a disaster is a strategic decision that directly affects the success of disaster response operations. Locating such facilities close to the disaster-prone areas is of utmost importance to minimize response time. However, this is also risky because the facility may be disrupted and hence may not support the demand point(s). In this study, we develop an optimization model that minimizes the risk that a demand point may be exposed to because it is not supported by the located facilities. The purpose is to choose the locations such that a reliable facility network to support the demand points is constructed. The risk for a demand point is calculated as the multiplication of the (probability of the) threat (e.g., earthquake), the vulnerability of the demand point (the probability that it is not supported by the facilities), and consequence (value or possible loss at the demand point due to threat). The vulnerability of a demand point is computed by using fault tree analysis and incorporated into the optimization model innovatively. To our knowledge, this paper is the first to use such an approach. The resulting non-linear integer program is linearized and solved as a linear integer program. The locations produced by the proposed model are compared to those produced by the p-center model with respect to risk value, coverage distance, and covered population by using several test problems. The model is also applied in a real problem. The results indicate that taking the risk into account explicitly may create significant differences in the risk levels. © 2014 Elsevier Ltd
A simulation model for military deployment
The Deployment Planning Problem (DPP) for military units may in general be defined as the problem of planning the movement of geographically dispersed military units from their home bases to their final destinations using different transportation assets and a multimodal transportation network while obeying the constraints of a time-phased force deployment data describing the movement requirements for troops and equipment. Our main contribution is to develop a GISbased, object-oriented, loosely-coupled, modular, platformindependent, multi-modal and medium-resolution discrete event simulation model to test the feasibility of deployment scenarios. While our simulation model is not a panacea for all, it allows creation and testing the feasibility of a given scenario under stochastic conditions and can provide insights into potential outcomes in a matter of a few hours. © 2007 IEEE
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