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July, 9 th 2010

Case Study 2 Providing decision support for the location of a new ABS facility producing electric cars Group 3 Alexandru Olteanu Thomas Veneziano Massimo Gurrieri Florian Schnetzer Sebastian Langton Yann Bouchery. July, 9 th 2010. Outline.

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July, 9 th 2010

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  1. Case Study 2 • Providing decision support for the location of a new ABS facility producing electric cars • Group 3 Alexandru Olteanu Thomas Veneziano • Massimo Gurrieri Florian Schnetzer • Sebastian Langton Yann Bouchery July, 9th 2010

  2. Outline • Definition of the problem: Country or site selection? • Problem structuring: from the decision context to the value tree • MCDA method • Results • Conclusions

  3. Definition of the problem • Identification of ABS’ main objective: • Selection of the “best” site for a new facility for the manufacturing of electric cars • Facility location problem literature review: • Clear distinction between country and site selection • Corollary • In the case study, the selected sites have been proposed after identifying suitable country “candidates”

  4. Problem structuring: ideal value tree

  5. Problem structuring: Data critique • Data-related challenges • Great quantities of heterogeneous data • Partly irrelevant, redundant, missing, incomplete data • Mainly country-oriented, little site-oriented data • Preference-related challenges • Eliciting preferences of the decision maker is not possible! Formulation of working hypothesis

  6. Problem Structuring: adapted value tree “Adapted value tree” and the relevant criteria with respect to available data and preferences:

  7. Problem Structuring CO1: Investment cost OE1: Taxation Index CO2: Production cost OE2: Automotive industry Index OE3: Stability Index HR1: Workforce Education Index OE4: Transport HR2: Workforce Skill Index OE5: Industrial infrastructure HR3: Unionization Index OE6: Living environment

  8. Chosen MCDA-method • Outranking methods preferred to MAVT-method • Application of “RUBIS” for solving the decision problem Reasons for our choice: • Dealing with impreciseness • Providing recommendations and potentially bad choices Approach: • Development of 4 different scenarios for weighting the criteria

  9. Results

  10. Conclusions • Which solution we can recommend:- Gora and Lavenec appear in three out of four scenarios; Paris, which is the best solution for one scenario is definitely too expensive • - Further analysis and complementing research on suggested sites • What could be improved for a better site selection:- Real life interaction with the decision maker during the whole process- Extension of the set of alternatives- Improve the quality and the completeness of the provided data

  11. THANK you G…

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