![](/images/graphics-bg.png)
An Improved Ant Colony Optimization Approach for Optimization of Process Planning
Joint Authors
Wang, JinFeng
Fan, XiaoLiang
Ding, Haimin
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-07-06
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Computer-aided process planning (CAPP) is an important interface between computer-aided design (CAD) and computer-aided manufacturing (CAM) in computer-integrated manufacturing environments (CIMs).
In this paper, process planning problem is described based on a weighted graph, and an ant colony optimization (ACO) approach is improved to deal with it effectively.
The weighted graph consists of nodes, directed arcs, and undirected arcs, which denote operations, precedence constraints among operation, and the possible visited path among operations, respectively.
Ant colony goes through the necessary nodes on the graph to achieve the optimal solution with the objective of minimizing total production costs (TPCs).
A pheromone updating strategy proposed in this paper is incorporated in the standard ACO, which includes Global Update Rule and Local Update Rule.
A simple method by controlling the repeated number of the same process plans is designed to avoid the local convergence.
A case has been carried out to study the influence of various parameters of ACO on the system performance.
Extensive comparative experiments have been carried out to validate the feasibility and efficiency of the proposed approach.
American Psychological Association (APA)
Wang, JinFeng& Fan, XiaoLiang& Ding, Haimin. 2014. An Improved Ant Colony Optimization Approach for Optimization of Process Planning. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-15.
https://search.emarefa.net/detail/BIM-1049113
Modern Language Association (MLA)
Wang, JinFeng…[et al.]. An Improved Ant Colony Optimization Approach for Optimization of Process Planning. The Scientific World Journal No. 2014 (2014), pp.1-15.
https://search.emarefa.net/detail/BIM-1049113
American Medical Association (AMA)
Wang, JinFeng& Fan, XiaoLiang& Ding, Haimin. An Improved Ant Colony Optimization Approach for Optimization of Process Planning. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-15.
https://search.emarefa.net/detail/BIM-1049113
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1049113