Ant Colony Algorithm for Assembly Sequence Planning of Large Space Truss Structures

2007 ◽  
Author(s):  
Jifeng Guo ◽  
Ping Wang ◽  
Naigang Cui
Keyword(s):  
Ant Colony Algorithm ◽  
Assembly Sequence Planning ◽  
Ant Colony ◽  
Truss Structures ◽  
Assembly Sequence ◽  
Large Space ◽  
Sequence Planning ◽  
Space Truss

An Ant Colony Algorithm for Integrating Assembly Sequence Planning and Assembly Line Balancing

2013 ◽  
Vol 397-400 ◽  
pp. 2570-2573 ◽  
Author(s):  
Zhuo Yang ◽  
Cong Lu ◽  
Hong Wang Zhao
Keyword(s):  
Ant Colony Algorithm ◽  
Assembly Line ◽  
Assembly Line Balancing ◽  
Assembly Sequence Planning ◽  
Ant Colony ◽  
Line Balancing ◽  
Assembly Planning ◽  
Planning Problem ◽  
Assembly Sequence ◽  
Sequence Planning

Assembly sequence planning (ASP) and assembly line balancing (ALB) problems are two essential problems in the assembly optimization. This paper proposes an ant colony algorithm for integrating assembly sequence planning and assembly line balancing, to deal with the two problems on parallel, and resolve the possible conflict between two optimization goals. The assembly sequence planning problem and the assembly line balancing problem are discussed, the process of the proposed ant colony algorithm is investigated. The results can provide a set of solutions for decision department in assembly planning.

Assembly Sequence Planning Including Tool Check Based on Improved Ant-Colony Algorithm

2013 ◽  
Vol 670 ◽  
pp. 3-9 ◽  
Author(s):  
R. Li ◽  
H. Chen ◽  
L. Xie
Keyword(s):  
Ant Colony Algorithm ◽  
Influence Factors ◽  
Assembly Sequence Planning ◽  
Ant Colony ◽  
Assembly Sequence ◽  
Sequence Planning ◽  
Precedence Relations ◽  
Assembly Sequences ◽  
Electromechanical Products ◽  
Improved Ant Colony Algorithm

According to the characteristics and demands of assembly sequence planning (ASP) of complicated electromechanical products, the improved Ant-Colony algorithm is presented to solve the problem. In order to plan assembly sequence, Precedence Graph, which is created based on assembly model, is created to record precedence relations between components. Several mechanisms are designed to make the precedence relations correct and compendious. To examine the feasibility of the sequences for tool’s operation, a quick checking method is proposed based on Potential Interference Information, which is created by simulating the tool’s movement and checking the interference information in entire assembly. Then, the Ant Colony Algorithm is improved to generate optimal assembly sequences with the guidance of precedence relations. Two important influence factors have been taken into account in the method. (1) A Penalty-Evaporation mechanism is proposed for the algorithm to punish unfeasible solutions. (2) Via analyzing the effects of the parameters in the state transfer function, the better solution is obtained while change the fixed parameters to transforming with time. Finally, an example illustrates the effectiveness of the strategy.

Assembly Sequence Planning Based on Connector Structure and Ant Colony Algorithm

2013 ◽  
Vol 712-715 ◽  
pp. 2482-2486 ◽  
Author(s):  
Ying Ying Su ◽  
Hai Dong ◽  
Di Liang
Keyword(s):  
Ant Colony Algorithm ◽  
Assembly Sequence Planning ◽  
Precedence Constraint ◽  
Ant Colony ◽  
Ant Algorithm ◽  
Assembly Sequence ◽  
Sequence Planning ◽  
Assembly Sequences ◽  
Assembly Unit ◽  
Optimal Assembly

For the purpose of effectively reducing the degree of complexity and improving the efficiency, the method of assembly sequence planning based on connector structure and ant algorithm was proposed. The concept of connector structure was presented, which was regarded as basic assembly unit to cover features of assembly parts. Then, a model of assembly sequence planning was built, which represented the precedence constraint relationship among connector structures. Additionally, the combination of the connector structure concept and characteristics of ant colony algorithm was developed for generating optimal assembly sequences under the guidance of precedence relations in the model. Finally, an example was studied to illustrate the effectiveness of the strategy.

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