Energy-efficient multi-objective flexible manufacturing scheduling

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F21%3A10246395" target="_blank" >RIV/61989100:27510/21:10246395 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S0959652620346540" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0959652620346540</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.jclepro.2020.124610" target="_blank" >10.1016/j.jclepro.2020.124610</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Energy-efficient multi-objective flexible manufacturing scheduling

Popis výsledku v původním jazyce

This paper presents a novel scheduling of a resource-constrained Flexible Manufacturing System (FMS) with consideration of the following sub-problems: (i) machine loading and unloading, (ii) manufacturing operation scheduling, (iii) machine assignment, and (iv) Automated Guided Vehicle (AGV) scheduling. In the proposed model, both the AGV and machinery are considered as the required resources. Energy efficiency of AGVs has been studied in order to improve environmental sustainability in terms of a linear function, which is based on load and distance, accordingly. Because of the NP-hard characteristics of the problem, a modified multi-objective particle swarm optimization (MMOPSO) has been developed for solving the model and compared with the classic version of the multi-objective particle swarm optimization (MOPSO) algorithm in terms of five performance metrics. Finally, the results are evaluated by the application of a multi-criteria decision-making (MCDM) algorithm according to which the MMOPSO outperforms the MOPSO. (C) 2020 Elsevier Ltd

Název v anglickém jazyce

Energy-efficient multi-objective flexible manufacturing scheduling

Popis výsledku anglicky

This paper presents a novel scheduling of a resource-constrained Flexible Manufacturing System (FMS) with consideration of the following sub-problems: (i) machine loading and unloading, (ii) manufacturing operation scheduling, (iii) machine assignment, and (iv) Automated Guided Vehicle (AGV) scheduling. In the proposed model, both the AGV and machinery are considered as the required resources. Energy efficiency of AGVs has been studied in order to improve environmental sustainability in terms of a linear function, which is based on load and distance, accordingly. Because of the NP-hard characteristics of the problem, a modified multi-objective particle swarm optimization (MMOPSO) has been developed for solving the model and compared with the classic version of the multi-objective particle swarm optimization (MOPSO) algorithm in terms of five performance metrics. Finally, the results are evaluated by the application of a multi-criteria decision-making (MCDM) algorithm according to which the MMOPSO outperforms the MOPSO. (C) 2020 Elsevier Ltd

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

50202 - Applied Economics, Econometrics

Projekt

<a href="/cs/project/GA18-15530S" target="_blank" >GA18-15530S: Multi Objective Optimization Application in Flexible Manufacturing and Project Scheduling Problems: Theory and Applications</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název periodika

Journal of Cleaner Production

ISSN

0959-6526

e-ISSN

—

Svazek periodika

283

Číslo periodika v rámci svazku

124610

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

14

Strana od-do

1-14

Kód UT WoS článku

000609032200015

EID výsledku v databázi Scopus

2-s2.0-85095826060