A species conservation technique was proposed in our research and a new algorithm, the Species Conservation Genetic Algorithm (SCGA), was established for finding the multi-global solutions of problems. We introduced SCGA to multimodal functions. The technique is based on dividing the population into several species according to their similarity. Each of these species is built around a dominating individual called the species seed Species seeds found in the current generation are saved (conserved) by moving them into the next generation.
Our technique has been proved to be very effective in finding multiple global solutions of multimodal optimization problems, which has been applied to a set of problems, including some problems known to be deceptive for genetic algorithms (GAs).
The general process of a species conservation genetic algorithm is
| Begin Initialize population Evaluate population Do while (not termination) Determine Species Selection Crossover Mutation Conserve Species loop End |
Parameters
| Determining method | There are three options:
|
| Conserving method | |
| Speceis Radius | |
| Maximum Species | The maximum number of Species |
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