| Input: MOPs: Multi-objective optimization problems; n: population size ; Gmax: Maximum Generation; |
| Output: A: Archive |
| 1. Generation counter t = 1. |
| 2. Initialization population
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| 3. Whilet < Gmax
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| 4. Set external archive At = ∅. |
| 5. Non-dominated sorting on Pt to obtain P∗
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| 6. For each xi ∈ Pt, i = 1, 2, …, n identify an exemplar |
| 7. Generate a new solution offspring OPt =solution generation ( xi) // Algorithm 4 |
| 8. Preserve the new solution P′ = OPt∪P∗
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| 9. Update the population Pt+1environmental selection (P′) // Algorithm 5 |
| 10. Update the archiveAt+1// Algorithm 6 |
| 11. End while
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