Evolving Generalized Solutions for Robust Multi-objective Optimization: Transportation Analysis in Disaster View Full Text


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Chapter Info

DATE

2019-02-03

AUTHORS

Keiki Takadama , Keiji Sato , Hiroyuki Sato

ABSTRACT

This paper proposes the multi-objective evolutionary algorithm (MOEA) that can evolve the generalized individuals, which include many solutions that can be applied into different situations with the minimal change. The intensive simulations on the waterbus route optimization problem as the real world problem have revealed the following implications: (1) the proposed MOEA cannot only optimize the solutions like general MOEAs but also can evolve the generalized individuals; and (2) the proposed MOEA can analyze the feature of the river transportation in the waterbus route optimization. More... »

PAGES

491-503

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-030-12598-1_39

DOI

http://dx.doi.org/10.1007/978-3-030-12598-1_39

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1111894734


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