Cargo Vessel Route Rationalization with Chimerical Genetic Algorithm
One of the most basic problems in logistics is the problem of route rationalization. Route rationalization may be based on different criterions, but at its core it always can be reduced to classic mathematical problems, such as travelling salesman problem (TSP). This study discusses methods, used to...
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Gdynia Maritime University
2020-12-01
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doaj-f3a11a4484cb41d08699439707a856062021-02-19T13:47:37ZengGdynia Maritime UniversityTransNav: International Journal on Marine Navigation and Safety of Sea Transportation2083-64732083-64812020-12-011441005100810.12716/1001.14.04.281088Cargo Vessel Route Rationalization with Chimerical Genetic AlgorithmAlexander KuznetsovG.B. PopovOne of the most basic problems in logistics is the problem of route rationalization. Route rationalization may be based on different criterions, but at its core it always can be reduced to classic mathematical problems, such as travelling salesman problem (TSP). This study discusses methods, used to find approximate solutions for TSP and proposes authors modification of classic genetic algorithm (GA) for solving vessel’s route rationalization problem. Test results and strategies for vessel’s route rationalization are discussed. A number of conclusions on best strategies for route rationalization is carried out.http://www.transnav.eu/files/Cargo Vessel Route Rationalization with Chimerical Genetic Algorithm,1088.pdfcargo vesselroute rationalizationcargo vessel route rationalizationgenetic algorithm (ga)chimerical genetic algorithmtravelling salesman problem (tsp)genetic algorithm (ga)sea ports |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Alexander Kuznetsov G.B. Popov |
spellingShingle |
Alexander Kuznetsov G.B. Popov Cargo Vessel Route Rationalization with Chimerical Genetic Algorithm TransNav: International Journal on Marine Navigation and Safety of Sea Transportation cargo vessel route rationalization cargo vessel route rationalization genetic algorithm (ga) chimerical genetic algorithm travelling salesman problem (tsp) genetic algorithm (ga) sea ports |
author_facet |
Alexander Kuznetsov G.B. Popov |
author_sort |
Alexander Kuznetsov |
title |
Cargo Vessel Route Rationalization with Chimerical Genetic Algorithm |
title_short |
Cargo Vessel Route Rationalization with Chimerical Genetic Algorithm |
title_full |
Cargo Vessel Route Rationalization with Chimerical Genetic Algorithm |
title_fullStr |
Cargo Vessel Route Rationalization with Chimerical Genetic Algorithm |
title_full_unstemmed |
Cargo Vessel Route Rationalization with Chimerical Genetic Algorithm |
title_sort |
cargo vessel route rationalization with chimerical genetic algorithm |
publisher |
Gdynia Maritime University |
series |
TransNav: International Journal on Marine Navigation and Safety of Sea Transportation |
issn |
2083-6473 2083-6481 |
publishDate |
2020-12-01 |
description |
One of the most basic problems in logistics is the problem of route rationalization. Route rationalization may be based on different criterions, but at its core it always can be reduced to classic mathematical problems, such as travelling salesman problem (TSP). This study discusses methods, used to find approximate solutions for TSP and proposes authors modification of classic genetic algorithm (GA) for solving vessel’s route rationalization problem. Test results and strategies for vessel’s route rationalization are discussed. A number of conclusions on best strategies for route rationalization is carried out. |
topic |
cargo vessel route rationalization cargo vessel route rationalization genetic algorithm (ga) chimerical genetic algorithm travelling salesman problem (tsp) genetic algorithm (ga) sea ports |
url |
http://www.transnav.eu/files/Cargo Vessel Route Rationalization with Chimerical Genetic Algorithm,1088.pdf |
work_keys_str_mv |
AT alexanderkuznetsov cargovesselrouterationalizationwithchimericalgeneticalgorithm AT gbpopov cargovesselrouterationalizationwithchimericalgeneticalgorithm |
_version_ |
1724261060119101440 |