Bacterial foraging optimization algorithm in robotic cells with sequence-dependent setup times

In this paper, we propose an improved discrete bacterial foraging algorithm to determine the optimal sequence of parts and robot moves in order to minimize the cycle time for the 2-machine robotic cell scheduling problem with sequence-dependent setup times. We present a method to convert the solutio...

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Main Authors: Majumder, Arindam, Laha, Dipak, Suganthan, Ponnuthurai Nagaratnam
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2021
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Online Access:https://hdl.handle.net/10356/152083
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1520832021-07-14T08:00:58Z Bacterial foraging optimization algorithm in robotic cells with sequence-dependent setup times Majumder, Arindam Laha, Dipak Suganthan, Ponnuthurai Nagaratnam School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering 2-machine Robotic Cell Sequencing of Parts In this paper, we propose an improved discrete bacterial foraging algorithm to determine the optimal sequence of parts and robot moves in order to minimize the cycle time for the 2-machine robotic cell scheduling problem with sequence-dependent setup times. We present a method to convert the solutions from continuous to discrete form. In addition, two neighborhood search techniques are employed to updating the positions of each bacterium during chemotaxis and elimination–dispersal operations in order to accelerate the search procedure and to improve the solution. Moreover, a multi-objective optimization algorithm based on NSGA-II combined with the response surface methodology and the desirability technique is applied to tune the parameters as well as to enhance the convergence speed of the proposed algorithm. Finally, a design of experiment based on central composite design is used to determine the optimal settings of the operating parameters of the proposed algorithm. The results of the computational experimentation with a large number of randomly generated test problems demonstrate that the proposed method is relatively more effective and efficient than the state-of-the-art algorithms in minimizing the cycle time in the robotic cell scheduling. We thank the reviewers for their detailed constructive comments on earlier versions of the draft to considerable improve the quality and presentation of the paper. 2021-07-14T08:00:58Z 2021-07-14T08:00:58Z 2019 Journal Article Majumder, A., Laha, D. & Suganthan, P. N. (2019). Bacterial foraging optimization algorithm in robotic cells with sequence-dependent setup times. Knowledge-Based Systems, 172, 104-122. https://dx.doi.org/10.1016/j.knosys.2019.02.016 0950-7051 https://hdl.handle.net/10356/152083 10.1016/j.knosys.2019.02.016 2-s2.0-85062448310 172 104 122 en Knowledge-Based Systems © 2019 Elsevier B.V. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
2-machine Robotic Cell
Sequencing of Parts
spellingShingle Engineering::Electrical and electronic engineering
2-machine Robotic Cell
Sequencing of Parts
Majumder, Arindam
Laha, Dipak
Suganthan, Ponnuthurai Nagaratnam
Bacterial foraging optimization algorithm in robotic cells with sequence-dependent setup times
description In this paper, we propose an improved discrete bacterial foraging algorithm to determine the optimal sequence of parts and robot moves in order to minimize the cycle time for the 2-machine robotic cell scheduling problem with sequence-dependent setup times. We present a method to convert the solutions from continuous to discrete form. In addition, two neighborhood search techniques are employed to updating the positions of each bacterium during chemotaxis and elimination–dispersal operations in order to accelerate the search procedure and to improve the solution. Moreover, a multi-objective optimization algorithm based on NSGA-II combined with the response surface methodology and the desirability technique is applied to tune the parameters as well as to enhance the convergence speed of the proposed algorithm. Finally, a design of experiment based on central composite design is used to determine the optimal settings of the operating parameters of the proposed algorithm. The results of the computational experimentation with a large number of randomly generated test problems demonstrate that the proposed method is relatively more effective and efficient than the state-of-the-art algorithms in minimizing the cycle time in the robotic cell scheduling.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Majumder, Arindam
Laha, Dipak
Suganthan, Ponnuthurai Nagaratnam
format Article
author Majumder, Arindam
Laha, Dipak
Suganthan, Ponnuthurai Nagaratnam
author_sort Majumder, Arindam
title Bacterial foraging optimization algorithm in robotic cells with sequence-dependent setup times
title_short Bacterial foraging optimization algorithm in robotic cells with sequence-dependent setup times
title_full Bacterial foraging optimization algorithm in robotic cells with sequence-dependent setup times
title_fullStr Bacterial foraging optimization algorithm in robotic cells with sequence-dependent setup times
title_full_unstemmed Bacterial foraging optimization algorithm in robotic cells with sequence-dependent setup times
title_sort bacterial foraging optimization algorithm in robotic cells with sequence-dependent setup times
publishDate 2021
url https://hdl.handle.net/10356/152083
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