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EMAPS II : AN EVOLUTIONARY ALGORITHM FOR MULTIOBJECTIVE OPTIMIZATION

2. Content. Aim of the StudyLiterature ReviewAn Evolutionary Algorithm-Fitness Function-Favorable Weights-Insertion and Replacement Rules-Ranking and Fitness Updates-Generating the Initial Set of SolutionsSteps of the Algorithm EMAPS IIComputational ResultsConclusion. 3. Aim of the St

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EMAPS II : AN EVOLUTIONARY ALGORITHM FOR MULTIOBJECTIVE OPTIMIZATION

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    1. 1 EMAPS II : AN EVOLUTIONARY ALGORITHM FOR MULTIOBJECTIVE OPTIMIZATION Banu Soylu & Murat Köksalan Industrial Engineering Department Middle East Technical University Ankara-TURKEY XI ELAVIO 2005

    2. 2 Content Aim of the Study Literature Review An Evolutionary Algorithm -Fitness Function -Favorable Weights -Insertion and Replacement Rules -Ranking and Fitness Updates -Generating the Initial Set of Solutions Steps of the Algorithm EMAPS II Computational Results Conclusion

    3. 3 Aim of the Study Develop an EA to approximate efficient frontier in Multiobjective Problems Goals (1) evolve towards the efficient frontier (2) evenly distribute over frontier & obtain a well-spread frontier

    4. 4

    5. 5 How to achieve the goals of the algorithm ? (1) Favor yourself over other members (2) Favor large distance from closest contender and Seed with good extreme solutions in each objective

    6. 6

    7. 7

    8. 8

    9. 9 Literature Review According to fitness assignment scheme;

    10. 10

    11. 11 Fitness Function

    12. 12 Fitness Function

    13. 13 Fitness Function

    14. 14 Favorable Weights

    15. 15 Favorable Weights

    16. 16

    17. 17 Insertion and Replacement Rules

    18. 18 Insertion and Replacement Rules

    19. 19 Ranking and Fitness Updates

    20. 20 Generating Initial Set of Solutions

    21. 21 EMAPS II Algorithm

    22. 22 Computational Results (Cont. Test Problems)

    23. 23 Computational Results (Cont. Test Problems)

    24. 24 Computational Results (Cont. Test Problems)

    25. 25 Computational Results (Cont. Test Problems)

    26. 26 Computational Results (Cont. Test Problems)

    27. 27 Computational Results (Cont. Test Problems)

    28. 28 Computational Results (Cont. Test Problems)

    29. 29 Computational Results (Cont. Test Problems)

    30. 30 Computational Results (Cont. Test Problems)

    31. 31 Computational Results (Cont. Test Problems)

    32. 32 Computational Results (Cont. Test Problems)

    33. 33 Computational Results (Cont. Test Problems)

    34. 34 Computational Results (MOKP Problem)

    35. 35 Computational Results (MOKP Problem)

    36. 36 Computational Results (MOKP Problem)

    37. 37 Computational Results (MOKP Problem)

    38. 38 Conclusions

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