An integrated approach to part selection and loading problem in FMS using genetic algorithm | |
| Author | Nguyen Van Duc |
| Call Number | AIT Thesis no.ISE-02-30 |
| Subject(s) | Genetic algorithms Flexible manufacturing systems |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering, School of Advanced Technologies |
| Publisher | Asian Institute of Technology |
| Series Statement | Thesis ; no. ISE-02-30 |
| Abstract | Part selection and machine loading are two major problems in the production planning of flexible manufacturing systems. There is a strong interdependence between two problems. If they are considered separately a solution of the part selection problem may make the resulting loading problem infeasible. Therefore an integrated approach that considers the part selection and loading problem simultaneously is proposed. A 0-1 integer linear programming model is formulated with the objective function to maximize the profits generated from producing a set of selected parts while allocating operations and associated cutting tools among the machines subject to the technological and capacity constrains of the manufacturing systems. The mathematical model is solved by the use of genetic algorithm. The GA strategy is developed in three parts: solution coding, solution generation and solution recombination. In solution coding the original binary routing variables are replaced by integer variables so that the chromosome length is reduced significantly. In solution generation, the level of feasibility is the main concern. The constraints are divided into two categories: direct and indirect. The direct constraints involve only two variables each and form the major chunk of constraints, they are easily satisfied by context-dependent genes. The remaining indirect constraints are handled by the penalty function approach. The solution recombination involves crossover and mutation. The crossover is performed in two steps, the part-gene swap followed by the routing swap, so that the feasibility level is not disturbed. With a similar intent, the mutation is allowed to operate only on selected genes. The GA is able to achieve optimum or near-optimum performance on a variety of experiments. A parametric study of GA factors is also carried out, indicating population size, selection method and termination criteria as influential parameters. |
| Year | 2002 |
| Corresponding Series Added Entry | Asian Institute of Technology. Thesis ; no. ISE-02-30 |
| Type | Thesis |
| School | School of Advanced Technologies (SAT) |
| Department | Department of Industrial Systems Engineering (DISE) |
| Academic Program/FoS | Industrial Systems Engineering (ISE) |
| Chairperson(s) | Bohez, Erik L. J.; |
| Examination Committee(s) | Voratas Kachitvichyanukul;Afzulpurkar, Nitin V.;Huynh Trung Luong; |
| Scholarship Donor(s) | Electricity of Vietnam; |
| Degree | Thesis (M.Eng.) - Asian Institute of Technology, 2002 |