1. Case study - Student selection for last year of Industrial Engineer at Politecnico di Roma MCDA Summer School 2010 Ecole Centrale de Paris Elise ARNAUD Karim LIDOUH Diclehan TEZCANER Mohamed HAMDAOUI Emmanuel PRADOS Naouel YOUSFI July 9, 2010

2. Agenda 1.Context 2.Aim 3.Decision process 4.Model description 5.Main steps 6.Conclusions 2Case study - Student selection

3. 1.Context The selection process is changing from paper based to paper based + interview Case study - Student selection3 Grades Cover letter CV Grades Cover letter CV Interview 

4. 2.Aim Affect at most 50 good students to the different groups while keeping these homogeneous – Numbers – Gender – Culture – Personalities Case study - Student selection4

5. 3.Decision process Sorting and ranking step – Separate students into categories – ‘Accepted’, ‘Recommended’ and ‘Rejected’ Assignment step – Use the obtained ranking and remaining information (gender, PT & P preferences) Case study - Student selection5

6. 4.Model description Alternatives – Students Decision makers – Two that act like one Case study - Student selection6

7. 4.Model description Criteria – Gap year – 3 rd year grades – 4 th year grades – Motivation – Personality – Project – Jobs – Professional track – Path – Gender – Culture – Personalities Case study - Student selection7 Evaluate good candidates Assign students to groups In case of problems

8. 4.Model description Case study - Student selection8

9. 4.Model description Methods – Sorting & ranking step: FlowSort 1 Weights – Elicited from the results of 2009 – Higher importance of 4 th year compared to 3 rd year – Lower importance of Motivation compared to other marks – Global higher importance of the marks compared to grades Case study - Student selection9 1.P. Nemery de Bellevaux and C. Lamboray (2008), FlowSort : a flow-based sorting method with limiting and central profiles. * TOP (*Official Journal of the Spanish Society of Statistics and Operations Research), Vol. 16-1, pp. 90-113. 3 rd year4 th yearMotivationPersonalityProjectJobs 5%15%10%22%23%27%

10. 4.Model description Importance of criteria (Decision tree 1 ) 10 1.Quinlan, J. R. (1993) C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers. Case study - Student selection

11. 4.Model description Parameters (FlowSort) Case study - Student selection11 Criterion3 rd yr4 th yrMotivationPersonalityProjectJobs Weight 5%15%10%22%23%27% Indifference thresh 000000 Preference thresh 1273333 Profile 1 30 5555 Profile 2 24273333 Profile 3 21252.5 Profile 4 18 1111

12. 4.Model description Profiles based on 2009 results (FlowSort) Case study - Student selection12

13. 4.Model description Validation of the model on 2009 results Case study - Student selection13

14. 5.Main steps Sorting of the 2010 students (using FlowSort) Case study - Student selection14

15. 5.Main steps Sorting of the 2010 students (using FlowSort) Case study - Student selection15 38 st. 3 st. 9 st.

16. 5.Main steps Assignment procedure – Affectation of the selected students to groups – Determine the capacity of each path for F/M Case study - Student selection16 Number of selected females Number of selected males

17. Algorithm (1) Start with student rank:1 (r=1) (2) If he/she has made a choice; For the gender (M/F) of the student, check path’s capacity If there is capacity, assign the student to the path Else go to the next choice Else, put the student to the waiting list (3) Let r = r+1. Continue with step 2. If student is in waiting list: affectation to the path with minimum students 17Case study - Student selection

18. An Example - Affectation Case study - Student selection18 PathFemale (Capacity:3) Male (Capacity:8) SCM1, 7, 92, 5 SFM36 IP4 MID8 If we have a student, Rank: 10 Female & Path : SCM Wait until all assignments are finished

19. Affectation to Paths for Students of 2010 Case study - Student selection 19 PathFemale (Capacity:3) Male (Capacity:8) Total (Capacity:11) SCM1, 14, 152, 5, 8, 10, 19, 20, 22, 2511 SFM3, 386, 13, 30, 32, 33, 36, 37, 40 10 IP 18, 26 4, 7, 11, 12, 17, 24, 27, 3510 MID16, 29, 39 23, 9, 21, 28, 31, 34, 41 10 5.Main steps

20. Step 1. Sorting in 3 groups ( Accepted, Recommended, Rejected ) Step 2. Ranking for the first 2 groups to present to the DM Step 3. Application of the assignment procedure Case study - Student selection20 6.Conclusions

21. Homogeneity  Number of students in each path, gender √  Cultures, variety of personalities X Number of selected students  Maximum of 50 from the best categories Case study - Student selection21

22. 6.Conclusions A student is rejected if – He/she cannot satisfy the minimum requirements – He/she is ranked below 50 A student cannot enter his/her preferred path if – The capacity is full with higher ranked students Case study - Student selection22

23. Thank you for your attention Case study - Student selection23

24. Appendices P ROMETHEE II Ranking (for the 2009 results) Case study - Student selection24

25. Appendices Tree rules (for the 2009 results) Case study - Student selection25

26. Appendices Decision tree (using results from our model) Case study - Student selection26

27. Appendices Tree rules (using results from our model) Case study - Student selection27

28. Appendices Case study - Student selection28 An example - Affectation If we have a student, Rank: 9 Female & Path : SCM PathFemale (Capacity:3) Male (Capacity:8) SCM1, 72, 5 SFM36 IP4 MID8