dc.contributor.author |
Pemarathne, W.P.J. |
|
dc.contributor.author |
Fernando, T.G.I. |
|
dc.date.accessioned |
2022-03-18T06:06:04Z |
|
dc.date.available |
2022-03-18T06:06:04Z |
|
dc.date.issued |
2020 |
|
dc.identifier.citation |
Pemarathne, W.P.J., Fernando, T.G.I.(2020). Optimising Electrical Wiring Design of a Single-Storey Floor Plan using Multi-Objective Ant Colony System Algorithm (MOACS-EWR), Vidyodaya Journal of Science Vol. 23 No. 01 (2020) 17-32 |
en_US |
dc.identifier.uri |
http://dr.lib.sjp.ac.lk/handle/123456789/10634 |
|
dc.description.abstract |
Nature-inspired algorithms are remarkable of producing optimum solutions by using the extraordinary behavior of nature. Ant colony optimisation algorithm is a foremost algorithm applied to various difficult combinatorial optimisation problems and proved successes. This research introduces a novel approach to optimise the electrical wire routes in the single-storey building through 2D walls. This study explores the applicability of Multi-Objective Ant Colony Algorithms for Electrical Wire Routing (MOACS-EWR) when optimizing the wire routes through the walls of a single-storey building. MOACS-EWR algorithm can optimise multiple objectives, length of the path and the number of bends in the path. The study was conducted using several models of rooms and finally the single-storey floor plan. Results show that MOACS-EWR algorithm can find the optimised wire routes in a floor plan. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
Faculty of Applied Sciences, University of Sri Jayewardenepura |
en_US |
dc.subject |
nature-inspired algorithms, ant colony optimisation algorithm, electrical wire routing, multi-objective optimisation, MOACS-EWR |
en_US |
dc.title |
Optimising Electrical Wiring Design of a Single-Storey Floor Plan using Multi-Objective Ant Colony System Algorithm (MOACS-EWR) |
en_US |
dc.type |
Article |
en_US |
dc.identifier.doi |
https://doi.org/10.31357/vjs.v23i01.4677 |
en_US |