FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2564112742> ?p ?o ?g. }

• W2564112742 endingPage "81" @default.
• W2564112742 startingPage "60" @default.
• W2564112742 abstract "Abstract The ability to maintain functionality in transport infrastructure is critical during disruptions. To ensure operational robustness in transportation networks, it is necessary to identify the most vital or critical roads (or links), then reinforce them to increase their resilience. In the literature, conventional approaches to analyze road network robustness have involved efforts to first remove selected road segments (one by one, not collectively), then measure the impact of these changes. Based on these results, the levels of impact are ranked and links that demonstrate the most significant impacts are deemed to be the most critical. One of the most significant limitations of such approaches, however, is that they disregard the combined effect of road connectivity. This study advances the state of knowledge in transportation-based resilience analysis through the development of an approach to assess the impact of “critical combination scenarios”. The methodology involves a two-phase process. The first phase is based on the sensor (loop detector) location problem, within which, a selected number of high demand roads are identified as “candidate” critical links. Then, the second phase employs a series of discrete network design problem (DNDP) to find a variety of critical combination scenarios. The DNDPs are solved based on a system optimal relaxation method using Bender’s Decomposition. Building further from these results, the extent to which a road network is robust (or fragile) is analyzed. The results of the DNDP solutions are demonstrated to be similar to a Lorenz Curve in which the area under the Lorenz Curve (in percentage) can be viewed as a global robustness index. This index can be used to compare and assess the robustness of different road networks and mitigation scenarios. To illustrate the practical utility of this method, this research applied the methodology to the Winnipeg, Canada road network." @default.
• W2564112742 created "2017-01-06" @default.
• W2564112742 creator A5003771294 @default.
• W2564112742 creator A5021264543 @default.
• W2564112742 creator A5023115482 @default.
• W2564112742 creator A5063359276 @default.
• W2564112742 date "2017-02-01" @default.
• W2564112742 modified "2023-10-01" @default.
• W2564112742 title "Identifying critical disruption scenarios and a global robustness index tailored to real life road networks" @default.
• W2564112742 cites W1964471896 @default.
• W2564112742 cites W1969967095 @default.
• W2564112742 cites W1974683893 @default.
• W2564112742 cites W1975320652 @default.
• W2564112742 cites W1977548549 @default.
• W2564112742 cites W1983860569 @default.
• W2564112742 cites W1984208669 @default.
• W2564112742 cites W1987769632 @default.
• W2564112742 cites W1991087299 @default.
• W2564112742 cites W1992374922 @default.
• W2564112742 cites W1993745812 @default.
• W2564112742 cites W1996643763 @default.
• W2564112742 cites W1999220758 @default.
• W2564112742 cites W2000219814 @default.
• W2564112742 cites W2002979629 @default.
• W2564112742 cites W2007893276 @default.
• W2564112742 cites W2010175274 @default.
• W2564112742 cites W2011209729 @default.
• W2564112742 cites W2019833157 @default.
• W2564112742 cites W2021250916 @default.
• W2564112742 cites W2038079205 @default.
• W2564112742 cites W2039836132 @default.
• W2564112742 cites W2044128787 @default.
• W2564112742 cites W2044951022 @default.
• W2564112742 cites W2045728330 @default.
• W2564112742 cites W2047875366 @default.
• W2564112742 cites W2048670190 @default.
• W2564112742 cites W2049741107 @default.
• W2564112742 cites W2052659776 @default.
• W2564112742 cites W2059499302 @default.
• W2564112742 cites W2061962896 @default.
• W2564112742 cites W2068373583 @default.
• W2564112742 cites W2069856409 @default.
• W2564112742 cites W2070207525 @default.
• W2564112742 cites W2070722739 @default.
• W2564112742 cites W2074987215 @default.
• W2564112742 cites W2080781471 @default.
• W2564112742 cites W2081120846 @default.
• W2564112742 cites W2081618840 @default.
• W2564112742 cites W2084129396 @default.
• W2564112742 cites W2085502150 @default.
• W2564112742 cites W2093244236 @default.
• W2564112742 cites W2093286150 @default.
• W2564112742 cites W2095818975 @default.
• W2564112742 cites W2096819890 @default.
• W2564112742 cites W2100938043 @default.
• W2564112742 cites W2104849445 @default.
• W2564112742 cites W2108658848 @default.
• W2564112742 cites W2110043546 @default.
• W2564112742 cites W2112269231 @default.
• W2564112742 cites W2113660803 @default.
• W2564112742 cites W2114158004 @default.
• W2564112742 cites W2115153093 @default.
• W2564112742 cites W2118751446 @default.
• W2564112742 cites W2122948491 @default.
• W2564112742 cites W2124659975 @default.
• W2564112742 cites W2131561578 @default.
• W2564112742 cites W2148606196 @default.
• W2564112742 cites W2154889564 @default.
• W2564112742 cites W2162544994 @default.
• W2564112742 cites W2170338278 @default.
• W2564112742 cites W2171985270 @default.
• W2564112742 cites W2254218369 @default.
• W2564112742 cites W2283453757 @default.
• W2564112742 cites W2283682293 @default.
• W2564112742 cites W2312921502 @default.
• W2564112742 cites W2334955119 @default.
• W2564112742 cites W2341407319 @default.
• W2564112742 cites W2382533298 @default.
• W2564112742 cites W2418011388 @default.
• W2564112742 cites W2510032770 @default.
• W2564112742 cites W2512479688 @default.
• W2564112742 cites W2520330486 @default.
• W2564112742 cites W4211111561 @default.
• W2564112742 cites W4251577648 @default.
• W2564112742 doi "https://doi.org/10.1016/j.tre.2016.12.003" @default.
• W2564112742 hasPublicationYear "2017" @default.
• W2564112742 type Work @default.
• W2564112742 sameAs 2564112742 @default.
• W2564112742 citedByCount "33" @default.
• W2564112742 countsByYear W25641127422017 @default.
• W2564112742 countsByYear W25641127422018 @default.
• W2564112742 countsByYear W25641127422019 @default.
• W2564112742 countsByYear W25641127422020 @default.
• W2564112742 countsByYear W25641127422021 @default.
• W2564112742 countsByYear W25641127422022 @default.
• W2564112742 countsByYear W25641127422023 @default.
• W2564112742 crossrefType "journal-article" @default.
• W2564112742 hasAuthorship W2564112742A5003771294 @default.

• next