Mobility Compass

Discover mobility and transportation research. Find experts, partners, networks.

  • About
  • Privacy Policy
  • Legal Notice
  • Contact

The Mobility Compass is an open tool for improving networking and interdisciplinary exchange within mobility and transport research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

To Graph

8.032 Topics available

To Map

944 Locations available

509.604 PEOPLE
509.604 People People
509.604 People

Show results for 509.604 people that are selected by your search filters.

←

Page 1 of 20385

→
←

Page 1 of 0

→
PeopleLocationsStatistics
Mouftah, Hussein T.
  • 1
  • 1
  • 2
  • 2025
Dugay, Fabrice
  • 3
  • 17
  • 6
  • 2025
Rettenmeier, Max
  • 4
  • 4
  • 28
  • 2025
Tomasch, ErnstGraz
  • 57
  • 166
  • 211
  • 2025
Cornaggia, Greta
  • 1
  • 4
  • 0
  • 2025
Palacios-Navarro, Guillermo
  • 1
  • 4
  • 2
  • 2025
Uspenskyi, Borys V.
  • 1
  • 3
  • 0
  • 2025
Khan, Baseem
  • 8
  • 38
  • 115
  • 2025
Fediai, Natalia
  • 6
  • 4
  • 6
  • 2025
Derakhshan, Shadi
  • 1
  • 0
  • 0
  • 2025
Somers, BartEindhoven
  • 13
  • 42
  • 246
  • 2025
Anvari, B.
  • 9
  • 31
  • 126
  • 2025
Kraushaar, SabineVienna
  • 2
  • 13
  • 0
  • 2025
Kehlbacher, Ariane
  • 10
  • 18
  • 14
  • 2025
Das, Raj
  • 3
  • 3
  • 17
  • 2025
Werbińska-Wojciechowska, Sylwia
  • 12
  • 12
  • 25
  • 2025
Brillinger, Markus
  • 4
  • 42
  • 4
  • 2025
Eskandari, Aref
  • 2
  • 13
  • 18
  • 2025
Gulliver, J.
  • 9
  • 74
  • 555
  • 2025
Loft, Shayne
  • 1
  • 9
  • 0
  • 2025
Kud, Bartosz
  • 1
  • 6
  • 0
  • 2025
Matijošius, JonasVilnius
  • 33
  • 89
  • 297
  • 2025
Piontek, Dennis
  • 6
  • 33
  • 30
  • 2025
Kene, Raymond O.
  • 2
  • 2
  • 30
  • 2025
Barbosa, Juliana
  • 3
  • 15
  • 11
  • 2025

Pelegrín, Blas

  • Google
  • 7
  • 9
  • 95

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (7/7 displayed)

  • 2023On the Existence and Computation of Nash Equilibrium in Network Competitive Location Under Delivered Pricing and Price Sensitive Demand1citations
  • 2018Computation of Multi-facility Location Nash Equilibria on a Network Under Quantity Competition10citations
  • 2016Profit maximization and reduction of the cannibalization effect in chain expansion12citations
  • 2012Isodistant points in competitive network facility location9citations
  • 2011Location strategy for a firm under competitive delivered prices12citations
  • 2008A practical algorithm for decomposing polygonal domains into convex polygons by diagonals12citations
  • 2007Planar Location and Design of a New Facility with Inner and Outer Competition: An Interval Lexicographical-like Solution Procedure39citations

Places of action

Chart of shared publication
García, María Dolores
3 / 4 shared
Fernández, Pascual
4 / 4 shared
García Pérez, María Dolores
1 / 2 shared
Suárez-Vega, Rafael
1 / 4 shared
Cano, Saúl
1 / 1 shared
Tóth, Boglárka
2 / 3 shared
Fernández, José
2 / 3 shared
Cánovas, Lázaro
1 / 2 shared
Plastria, Frank
1 / 17 shared
Chart of publication period
2023
2018
2016
2012
2011
2008
2007

Co-Authors (by relevance)

  • García, María Dolores
  • Fernández, Pascual
  • García Pérez, María Dolores
  • Suárez-Vega, Rafael
  • Cano, Saúl
  • Tóth, Boglárka
  • Fernández, José
  • Cánovas, Lázaro
  • Plastria, Frank
OrganizationsLocationPeople

document

Isodistant points in competitive network facility location

  • Suárez-Vega, Rafael
  • Cano, Saúl
  • Pelegrín, Blas

Abstract

An isodistant point is any point on a network which is located at a predetermined distance from some node. For some competitive facility location problems on a network, it is verified that optimal (or near-optimal) locations are found in the set of nodes and isodistant points (or points in the vicinity of isodistant points). While the nodes are known, the isodistant points have to be determined for each problem. Surprisingly, no algorithm has been proposed to generate the isodistant points on a network. In this paper, we present a variety of such problems and propose an algorithm to find all isodistant points for given threshold distances associated with the nodes. The number of isodistant points is upper bounded by nm , where n and m are the number of nodes and the number of edges, respectively. Computational experiments are presented which show that isodistant points can be generated in short run time and the number of such points is much smaller than nm . Thus, for networks of moderate size, it is possible to find optimal (or near-optimal) solutions through the Integer Linear Programming formulations corresponding to the discrete version of such problems, in which a finite set of points are taken as location candidates.

Topics

  • optimisation
  • decision theory
  • operations research
  • theory
  • algorithm
  • Statistic
  • economics
  • production
  • industrial engineering
  • hub
  • experiment
  • linear programming
  • insurance
  • finance
  • Paea
  • Pifa
  • Pg
  • Pagb
  • Pafc
  • Odgc
  • Ocg
  • Ak
  • Oefk
  • Tahdcaaa
  • Ef
  • Paaab
  • Ai
  • Ae

Search in FID move catalog