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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