Abstract
A New Population-Oriented Simulated Annealing (NPOSA) technique is introduced here as an efficient global search tool to solve optimization problems. Unlike the conventional SA or its hybrid algorithms, each individual in the population can intelligently plan its own annealing schedule in an adaptive fashion to the given problem at hand. This not only enhances the search speed but further, yields a solution near the global optimum. This technique has been applied to solve the Traveling Salesman Problem (TSP) for combinatorial optimization as well as a continuous function optimization problem to demonstrate its validity and effectiveness.
| Original language | English |
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| Pages | 598-602 |
| Number of pages | 5 |
| State | Published - 1998 |
| Event | Proceedings of the 1998 IEEE International Conference on Evolutionary Computation, ICEC'98 - Anchorage, AK, USA Duration: 4 May 1998 → 9 May 1998 |
Conference
| Conference | Proceedings of the 1998 IEEE International Conference on Evolutionary Computation, ICEC'98 |
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| City | Anchorage, AK, USA |
| Period | 4/05/98 → 9/05/98 |