Minimizing energy consumption in a straight robotic assembly line using differential evolution algorithm

Mukund Nilakantan Janardhanan*, Peter Nielsen, Zixiang Li, S. G. Ponnambalam

*Kontaktforfatter

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2 Citationer (Scopus)

Abstract

This paper focuses on implementing differential evolution (DE) to optimize the robotic assembly line balancing (RALB) problems with an objective of minimizing energy consumption in a straight robotic assembly line and thereby help to reduce energy costs. Few contributions are reported in literature addressing this problem. Assembly line balancing problems are classified as NP-hard, implying the need of using metaheuristics to solve realistic sized problems. In this paper, a well-known metaheuristic algorithm differential evolution is utilized to solve the problem. The proposed algorithm is tested on benchmark problems and the obtained results are compared with current state. It can be seen that the proposed DE algorithm is able to find a better solution for the considered objective function. Comparison of the computational time along with the cycle time is presented in detail.

OriginalsprogEngelsk
TitelDistributed Computing and Artificial Intelligence, 14th International Conference
Antal sider8
ForlagSpringer
Publikationsdato1 jan. 2018
Sider45-52
ISBN (Trykt)978-3-319-62409-9
ISBN (Elektronisk)978-3-319-62410-5
DOI
StatusUdgivet - 1 jan. 2018
Begivenhed14th International Symposium on Distributed Computing and Artificial Intelligence, DCAI 2017 - Porto, Portugal
Varighed: 21 jun. 201723 jun. 2017

Konference

Konference14th International Symposium on Distributed Computing and Artificial Intelligence, DCAI 2017
Land/OmrådePortugal
ByPorto
Periode21/06/201723/06/2017
NavnAdvances in Intelligent Systems and Computing
Vol/bind620
ISSN2194-5357

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