The Improved Ant Colony Optimization Algorithm for MLP considering the Advantage from Relationship

Yabo Luo and Yongo P. Waden

Mathematical Problems in Engineering, 2017, vol. 2017, 1-11

Abstract:

An improved ant colony optimization (ACO) is presented to solve the machine layout problem (MLP), and the concept is categorized as follows: firstly, an ideology on “advantage from quantity” and “advantage from relationship” is proposed and an example is demonstrated. In addition, the strategy of attached variables under local polar coordinate systems is employed to maintain search efficiency, that is, “advantage from relationship”; thus, a mathematical model is formulated under a single rectangular coordinate system in which the relative distance and azimuth between machines are taken as attached design variables. Further, the aforementioned strategies are adopted into the ant colony optimization (ACO) algorithm, thereby employing the inverse feedback mechanism for dissemination of pheromone and the positive feedback mechanism for pheromone concentration. Finally, the effectiveness of the proposed improved ACO is tested through comparative experiments, in which the results have shown both the reliability of convergence and the improvement in optimization degree of solutions.

Date: 2017
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/MPE/2017/3920327.pdf (application/pdf)
http://downloads.hindawi.com/journals/MPE/2017/3920327.xml (text/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:3920327

DOI: 10.1155/2017/3920327

Access Statistics for this article

More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().