Transport network analysis: Difference between revisions

Revision as of 08:05, 17 March 2021

Revision as of 08:07, 17 March 2021

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==Analysis Methods==

A wide range of methods, algorithms, and techniques have been developed for solving problems and tasks relating to network flow. Some of these are common to all types of transport networks, while others are specific to particular application domains.<ref>{{cite book |last1=deSmith |first1=Michael J. |last2=Goodchild |first2=Michael F. |last3=Longley |first3=Paul A. |title=Geospatial Analysis: A Comprehensive Guide to Principles, Techniques, and Software Tools |date=2021 |edition=6th revised |chapter-title=7.2.1 Overview - network and locational analysis | chapter-url=https://www.spatialanalysisonline.com/HTML/index.html?overview_-_network_analysis.htm}}</ref> Many of these algorithms are implemented in commercial and open-source GIS software, such as [[GRASS GIS]] and the Network Analyst extension to Esri [[ArcGIS]].

===Optimal routing===

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{{main | Facility ___location problem | Location-allocation}}

This class of problems aims to find the optimal ___location for one or more facilities along the network, with ''optimal'' defined as minimizing the aggregate or mean travel cost to (or from) another set of points in the network. A common example is determining the ___location of a warehouse to minimize shipping costs to a set of retail outlets, or the ___location of a retail outlet to minimize the travel time from the residences of its potential customers. In unconstrained (cartesian coordinate) space, this is an NP-hard problem requiring heuristic solutions such as [[Lloyd's algorithm]], but in a network space it can be solved deterministically.<ref>{{cite book |last1=deSmith |first1=Michael J. |last2=Goodchild |first2=Michael F. |last3=Longley |first3=Paul A. |title=Geospatial Analysis: A Comprehensive Guide to Principles, Techniques, and Software Tools |date=2021 |edition=6th revised |chapter-title=7.4.2 Larger p-median and p-center problems | chapter-url=https://www.spatialanalysisonline.com/HTML/index.html?larger_p-median_and_p-center_p.htm}}</ref>

Particular applications often add further constraints to the problem, such as the ___location of pre-existing or competing facilities, facility capacities, or maximum cost.

===Service areas===

A network service area is analogous to a [[Buffer (GIS) | buffer]] in unconstrained space, a depiction of the area that can be reached from a point (typically a service facility) in less than a specified distance or other accumulated cost.<ref>{{cite book |last1=deSmith |first1=Michael J. |last2=Goodchild |first2=Michael F. |last3=Longley |first3=Paul A. |title=Geospatial Analysis: A Comprehensive Guide to Principles, Techniques, and Software Tools |date=2021 |edition=6th revised |chapter-title=7.4.3 Service areas | chapter-url=https://www.spatialanalysisonline.com/HTML/index.html?service_areas.htm}}</ref> For example, the preferred service area for a fire station would be the set of street segments it can reach in a small amount of time. When there are multiple facilities, each edge would be assigned to the nearest facility, producing a result analogous to a [[Voronoi diagram]].<ref>{{cite web |title=v.net.alloc command |url=https://grass.osgeo.org/grass78/manuals/v.net.alloc.html |website=GRASS GIS documentation |publisher=OSGEO |access-date=17 March 2021}}</ref>

===Fault analysis===