The Assignment Problem and Its Relation to Logistics Problems

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F22%3APU145892" target="_blank" >RIV/00216305:26210/22:PU145892 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.mdpi.com/1999-4893/15/10/377" target="_blank" >https://www.mdpi.com/1999-4893/15/10/377</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/a15100377" target="_blank" >10.3390/a15100377</a>

Jazyk výsledku

angličtina

Název v původním jazyce

The Assignment Problem and Its Relation to Logistics Problems

Popis výsledku v původním jazyce

The assignment problem is a problem that takes many forms in optimization and graph theory, and by changing some of the constraints or interpreting them differently and adding other constraints, it can be converted to routing, distribution and scheduling problems. Showing such correlations is one of the aims of this paper. Some of the derived problems having exponential time complexity, the question arises of their solvability for larger instances. Instead of the traditional approach based on the use of approximate or stochastic heuristic methods, we focus here on the direct use of mixed integer programming models in the GAMS environment, which is now capable of solving instances much larger than in the past and does not require complex parameter settings or statistical evaluation of the results as in the case of stochastic heuristics because the computational core of software tools, nested in GAMS, is deterministic in nature. The source codes presented may be an aid, because this tool is not yet as well known as the MATLAB Optimisation Toolbox. Benchmarks of the permutation flow shop scheduling problem with informally derived MIP model and the travelling salesman problem are used to present the limits of the software’s applicability.

Název v anglickém jazyce

The Assignment Problem and Its Relation to Logistics Problems

Popis výsledku anglicky

The assignment problem is a problem that takes many forms in optimization and graph theory, and by changing some of the constraints or interpreting them differently and adding other constraints, it can be converted to routing, distribution and scheduling problems. Showing such correlations is one of the aims of this paper. Some of the derived problems having exponential time complexity, the question arises of their solvability for larger instances. Instead of the traditional approach based on the use of approximate or stochastic heuristic methods, we focus here on the direct use of mixed integer programming models in the GAMS environment, which is now capable of solving instances much larger than in the past and does not require complex parameter settings or statistical evaluation of the results as in the case of stochastic heuristics because the computational core of software tools, nested in GAMS, is deterministic in nature. The source codes presented may be an aid, because this tool is not yet as well known as the MATLAB Optimisation Toolbox. Benchmarks of the permutation flow shop scheduling problem with informally derived MIP model and the travelling salesman problem are used to present the limits of the software’s applicability.

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

2022

Kód důvěrnosti údajů

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

Název periodika

Algorithms

ISSN

1999-4893

e-ISSN

—

Svazek periodika

15

Číslo periodika v rámci svazku

10

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

27

Strana od-do

1-27

Kód UT WoS článku

000872041000001

EID výsledku v databázi Scopus

2-s2.0-85140395403