Abstract
Summary form only given. Assigning a new product to a production line is one of many problems whose solution is very complex and is approached by either exact mathematical programming or quick heuristics. The solution proposed imitates a foreman's decision when he faces a real problem. A perceptron-type neural network is developed whose input parameters are a function of planning data, real-time status, and local expertise. Its output is the foreman's decision. The robustness of this approach is demonstrated by a case study.
| Original language | English |
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| Pages | 577 |
| Number of pages | 1 |
| State | Published - 1989 |
| Event | IJCNN International Joint Conference on Neural Networks - Washington, DC, USA Duration: 18 Jun 1989 → 22 Jun 1989 |
Conference
| Conference | IJCNN International Joint Conference on Neural Networks |
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| City | Washington, DC, USA |
| Period | 18/06/89 → 22/06/89 |