Genetic Algorithm for the Continuous Location-Routing Problem

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21260%2F19%3A00332245" target="_blank" >RIV/68407700:21260/19:00332245 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.14311/NNW.2019.29.012" target="_blank" >https://doi.org/10.14311/NNW.2019.29.012</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.14311/NNW.2019.29.012" target="_blank" >10.14311/NNW.2019.29.012</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Genetic Algorithm for the Continuous Location-Routing Problem

Popis výsledku v původním jazyce

This paper focuses on the continuous location-routing problem that comprises of the location of multiple depots from a given region and determining the routes of vehicles assigned to these depots. The objective of the problem is to design the delivery system of depots and routes so that the total cost is minimal. The standard location-routing problem considers a finite number of possible locations. The continuous location-routing problem allows location to infinite number of locations in a given region and makes the problem much more complex. We present a genetic algorithm that tackles both location and routing subproblems simultaneously.

Název v anglickém jazyce

Genetic Algorithm for the Continuous Location-Routing Problem

Popis výsledku anglicky

This paper focuses on the continuous location-routing problem that comprises of the location of multiple depots from a given region and determining the routes of vehicles assigned to these depots. The objective of the problem is to design the delivery system of depots and routes so that the total cost is minimal. The standard location-routing problem considers a finite number of possible locations. The continuous location-routing problem allows location to infinite number of locations in a given region and makes the problem much more complex. We present a genetic algorithm that tackles both location and routing subproblems simultaneously.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10102 - Applied mathematics

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Neural Network World

ISSN

1210-0552

e-ISSN

—

Svazek periodika

29

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

15

Strana od-do

173-187

Kód UT WoS článku

000475843600004

EID výsledku v databázi Scopus

2-s2.0-85070204786