Team 2056 Page 4 of 50 5.6 Genetic Algorithm Applied to a Random Seating Ar- rangement 5.7 Seeded Genetic Algorithm 5.8 Deplaning 5.9 Sensitivity and Robustness Testing 5.9.1 Baggage 5.9.2 Seat collision 5.9.3 Queuing 6 Discussion and conclusions 6. 1 Executive Summary 6. 1.1 Boarding Sequences and Results 6.1.2 Further Optimization 6.1.3 Organizational Change Management and Cus- tomer Relationship management 6.2 Strengths and Weaknesses 6.3 Future Work 7 Appendices 7.1 Appendix A: Past Work 7.2 Appendix B: Preliminary Model 7.3 Appendix C: Definitions and ComputationsTeam 2056 Page 4 of 50 5.6 Genetic Algorithm Applied to a Random Seating Ar￾rangement . . . . . . . . . . . . . . . . . . . . . . . . 36 5.7 Seeded Genetic Algorithm . . . . . . . . . . . . . . . 37 5.8 Deplaning . . . . . . . . . . . . . . . . . . . . . . . . 37 5.9 Sensitivity and Robustness Testing . . . . . . . . . . 38 5.9.1 Baggage . . . . . . . . . . . . . . . . . . . . . 38 5.9.2 Seat collisions . . . . . . . . . . . . . . . . . . 39 5.9.3 Queuing . . . . . . . . . . . . . . . . . . . . . 39 6 Discussion and Conclusions 39 6.1 Executive Summary . . . . . . . . . . . . . . . . . . . 39 6.1.1 Boarding Sequences and Results . . . . . . . . 40 6.1.2 Further Optimization . . . . . . . . . . . . . . 41 6.1.3 Organizational Change Management and Cus￾tomer Relationship Management . . . . . . . 42 6.2 Strengths and Weaknesses . . . . . . . . . . . . . . . 42 6.3 Future Work . . . . . . . . . . . . . . . . . . . . . . . 43 7 Appendices 45 7.1 Appendix A: Past Work . . . . . . . . . . . . . . . . 45 7.2 Appendix B: Preliminary Model . . . . . . . . . . . . 47 7.3 Appendix C: Definitions and Computations . . . . . 48