The Role of Fuzzy and Genetic Algorithms in Part Family Formation and Sequence Optimisation for Flexible Manufacturing Systems
| Autor: | K. Chandra Sekhara Rao, K. S. Ravichandran, R. Saravanan |
|---|---|
| Rok vydání: | 2002 |
| Předmět: |
Sequence
Mathematical optimization Mechanical Engineering Fuzzy set Flexible manufacturing system Fuzzy logic Industrial and Manufacturing Engineering Similitude Computer Science Applications Group technology Control and Systems Engineering Genetic algorithm Cluster analysis Algorithm Software Mathematics |
| Zdroj: | The International Journal of Advanced Manufacturing Technology. 19:879-888 |
| ISSN: | 1433-3015 0268-3768 |
| DOI: | 10.1007/s001700200100 |
| Popis: | 1. A new similarity coefficient measure has been developed and this coefficient measure is used to form a part-family. 2. A mathematical model that uses this similarity coefficient for solving the part-family formation problems optimally in an FMS is developed. The fuzzy approach has the special advantage of producing more accurate results than conventional clustering and other methods. It not only reveals the specific part family that a part belongs to, but also provides the degree of membership of a part associated with each part family. This will give a balanced work load for the machine. In the second part of this paper, the introduction of the concept of genetic algorithms is proposed to eliminate more job sequences and, finally, the optimum sequence is obtained through the minimum penalty cost. Software is developed and implemented to obtain an optimum sequence and, finally, a numerical example is given as an illustration. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full text from SpringerLink