What is it about?
This paper describes an improved method for finding the shortest path between two points positioned within a space defined by multiple continuous costs. This method works by using a computational procedure that mimics the biological process of evolutionary natural selection to deliver a set of near-optimal solutions to this corridor location problem.
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Why is it important?
The corridor location problem is a very generic problem class which appears in a wide range of contexts ranging from planning and engineering to operations research and computer engineering. The method which is described in the paper is useful in the extent to which the user is able to explicitly control the tradeoff between solution quality and computational effort, thus allowing it to be applied to previously untenable problem sizes or to planning situations where rough initial solutions must be generated quickly and with minimal effort.
Perspectives
I believe that the refinements to the corridor location algorithm - and the associated open source implementation - introduced in this paper, will make the genetic approach not just a viable option for solving large scale real world corridor location problems, but indeed the most attractive means for solving these types of problems within a planning context. As such, I am excited to see how this refined approach will be used to improve the outcome of planning problems that require the generation of low-cost or low-impact corridors and throughways.
Dr Eric Daniel Fournier
UCSB
Read the Original
This page is a summary of: MOGADOR revisited: Improving a genetic approach to multi-objective corridor search, Environment and Planning B Planning and Design, December 2015, SAGE Publications,
DOI: 10.1177/0265813515618562.
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