5574790
doi
10.35940/ijeat.C5410.029320
oai:zenodo.org:5574790
Blue Eyes Intelligence Engineering & Sciences Publication (BEIESP)
Publisher
S. Vara Kumari
Department of E C E, K L E F University, Guntur, AP, 522501, India.
P. Manohar
Department of Mechanical Engineering, K L E F University, Guntur, AP, India
B. Madesh
Department of Mechanical Engineering, K L E F University, Guntur, AP, India
P. Naveen Krishna
Department of Mechanical Engineering, K L E F University, Guntur, AP, India
R. Suraj Krishna Sai
Department of Mechanical Engineering, K L E F University, Guntur, AP, India
Simultaneous Scheduling of Machines and AGVs in FMS Through Ant Colony Optimization Algorithm
M. Nageswara Rao
Department of Mechanical Engineering, K L E F University, Guntur, AP, India
issn:2249-8958
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
FMS; Operational Completion Time (makespan); Metaheuristic algorithms; AGVs; NP-hard problems.
<p>High amount of flexibility and quick response times have become essential features of modern manufacturing systems where customers are demanding a variety of products with reduced product life cycles. Flexible manufacturing system (FMS) is the right choice to achieve these challenging tasks. The performance of FMS is dependent on the selection of scheduling policy of the manufacturing system. In Traditional scheduling problems machines are as considered alone. But material handling equipment’s are also valuable resources in FMS. The scheduling of AGVs is needed to be optimized and harmonized with machine operations. Scheduling in FMS is a well-known NP-hard problem due to considerations of material handling and machine scheduling. Many researchers addressed machine and AGVs individually. In this work an attempt is made to schedule both the machines and AGVs simultaneously. For solving these problems-a new metaheuristic Ant Colony Optimization (ACO) algorithm is proposed.</p>
Zenodo
2020-02-29
info:eu-repo/semantics/article
5574789
1634564923.366807
553849
md5:dd5a2312c3504028b34a56af1dd3d8b9
https://zenodo.org/records/5574790/files/C5410029320 (1).pdf
public
2249-8958
Is cited by
issn
International Journal of Engineering and Advanced Technology (IJEAT)
9
3
1392-1397
2020-02-29