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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | da Fonseca, J.B. |
| Copyright Year | 2006 |
| Description | Author affiliation: Dept. of Electr. Eng. & Comput. Sci., New Univ. of Lisbon, Monte de Caparica (da Fonseca, J.B.) |
| Abstract | In a previous work we presented an algorithm inspired in the Strong Artificial Intelligence and in the minimax optimization that imitates the human being in the solution of the magic square and we showed that in most cases its performance was better than the human's performance and even better than the performance of the best algorithms to solve the magic square, in terms of number of changes. In this paper we adapt and transform this algorithm to solve the optimization of an AGVs network problem, using as a first test case 9 workstations in fixed positions and 9 operations to be executed, and the optimization problem is translated in the search of which of the 9! possible manners to distribute 9 operations by the 9 workstations that minimizes the total production time for a given plan of production. Finally we considered the more general case where the number of workstations is greater than the number of operations, and so there are some workstations that make the same operation, and we will have a layout with repetitions and multiple trajectories that implement the same product. |
| Starting Page | 181 |
| Ending Page | 181 |
| File Size | 240507 |
| Page Count | 1 |
| File Format | |
| ISBN | 0769527310 |
| DOI | 10.1109/CIMCA.2006.101 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-11-28 |
| Publisher Place | Australia |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Humans Production Evolutionary computation Minimax techniques Explosives Workstations Artificial intelligence Flexible manufacturing systems Computational intelligence Testing |
| Content Type | Text |
| Resource Type | Article |
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