Scheduling of mobile robots for transportation and manufacturing tasks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F19%3A00108859" target="_blank" >RIV/00216224:14330/19:00108859 - isvavai.cz</a>

Výsledek na webu

<a href="http://doi.org/10.1007/s10732-018-9391-z" target="_blank" >http://doi.org/10.1007/s10732-018-9391-z</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s10732-018-9391-z" target="_blank" >10.1007/s10732-018-9391-z</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Scheduling of mobile robots for transportation and manufacturing tasks

Popis výsledku v původním jazyce

Current manufacturing systems have a tendency to become more and more flexible to adapt to the needs of product diversification. Such a system, e.g. flexible manufacturing system, consists of a number of automatic machines, material handling devices such as automated guided vehicles (AGVs) or mobile robots, and a central control computer. Mobile robots, as well as AGVs, can move around in their working space to transport components among machines. The main novelty of this work is that mobile robots can also execute various value-added tasks without human intervention thanks to their manipulation arms which is not possible for AGVs. This new characteristic certainly makes the problem more complex and computationally expensive. To utilize these manufacturing systems in an efficient manner, it is necessary to schedule transportation of product components by mobile robots and to schedule processing of products on machines possibly by mobile robots. Consequently, the key innovation of this work lies in consideration of three interrelated sub-problems which must be solved. They include computing the sequence of operations on machines, the robot assignment for transportation, and the robot assignment for processing. To achieve this goal, a computationally efficient hybrid heuristic method combining genetic algorithm and tabu search is developed to solve the problem considering makespan minimization. A mixed-integer programming (MIP) model is formulated. Another combined method using results of the hybrid heuristic is proposed to speed up the solving of MIP model. The quality of hybrid heuristic’s solutions is compared and evaluated by using those of the MIP model as reference points.

Název v anglickém jazyce

Scheduling of mobile robots for transportation and manufacturing tasks

Popis výsledku anglicky

Current manufacturing systems have a tendency to become more and more flexible to adapt to the needs of product diversification. Such a system, e.g. flexible manufacturing system, consists of a number of automatic machines, material handling devices such as automated guided vehicles (AGVs) or mobile robots, and a central control computer. Mobile robots, as well as AGVs, can move around in their working space to transport components among machines. The main novelty of this work is that mobile robots can also execute various value-added tasks without human intervention thanks to their manipulation arms which is not possible for AGVs. This new characteristic certainly makes the problem more complex and computationally expensive. To utilize these manufacturing systems in an efficient manner, it is necessary to schedule transportation of product components by mobile robots and to schedule processing of products on machines possibly by mobile robots. Consequently, the key innovation of this work lies in consideration of three interrelated sub-problems which must be solved. They include computing the sequence of operations on machines, the robot assignment for transportation, and the robot assignment for processing. To achieve this goal, a computationally efficient hybrid heuristic method combining genetic algorithm and tabu search is developed to solve the problem considering makespan minimization. A mixed-integer programming (MIP) model is formulated. Another combined method using results of the hybrid heuristic is proposed to speed up the solving of MIP model. The quality of hybrid heuristic’s solutions is compared and evaluated by using those of the MIP model as reference points.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2019

Kód důvěrnosti údajů

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

Název periodika

Journal of Heuristics

ISSN

1381-1231

e-ISSN

1572-9397

Svazek periodika

25

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

39

Strana od-do

175-213

Kód UT WoS článku

000459192400002

EID výsledku v databázi Scopus

2-s2.0-85053278539