Research Article
A Guiding Evolutionary Algorithm with Greedy Strategy for Global Optimization Problems
| Initialize the population , and define limit parameter , | | scope of mutation , range of local search | | Evaluate the initialized population | | Select the best individual | | While () | | For each individual | | Make crossover to generate a new individual | | If () | | Make mutation for | | | | If () | | Make local search for | | | | If ( is better than ) | | Accept this new individual | | | | If ( is better than ) | | Replace using | | | | | | | | Output results and visualization |
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