MS-E2191 - Graduate Seminar on Operations Research (V) D, Lecture, 17.9.2021-10.12.2021
This course space end date is set to 10.12.2021 Search Courses: MS-E2191
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Date Presenter Pres.-# Topic & slides (slide template) Material Home assignment model solution Opponents 17.9. Antti Punkka 0 Introduction of the seminar: working principles, etc. - - - 17.9. Miku Vilander 1 Benefit-to-cost analysis and optimization models in project portfolio selection Kirkwood (1997): 199-211 and 216-222, Kleinmuntz (2007), Brown et al. (2004) model solution 24.9. Aleksi Avela 2 Additive value functions: attribute-specific value functions, conditions required, attribute weights, elicitation Eisenführ et al. (2010): 107-142, 151-154, MS-E2134 lecture material model solution Kontio, Korkealaakso 24.9. Thomas Holt 3 Additive-linear portfolio value function: theory and an application Golabi ym. (1981), see also Liesiö (2014) model solution Laine, Vilander 1.10. Konsta Holopainen 4 Applications of using additive-linear portfolio value function Ewing et al. (2006), Kleinmuntz and Kleinmuntz (1999) model solution Anttila, Avela 1.10. Helmiina Kontio 5 Preference Programming methods: Incomplete preference information for additive value functions; elicitation, modeling, decision recommendations Salo and Hämäläinen (2010, 1992, 2001), Mustajoki et al. (2005), [Eisenführ et al. (2010): 144-149], Punkka and Salo (2013, 2014) model solution Holt, Mäkinen 8.10. Helmi Hankimaa 6 Preference Programming in portfolio decision analysis: The Robust Portfolio Modeling method Liesiö et al. (2007, 2008) model solution Rosenberg, Staudinger 8.10. Tommi Anttila 7 Baseline values and an application of Robust Portfolio Modeling Mild et al. (2015), Clemen and Smith (2009), Liesiö and Punkka (2014) model solution Uusihärkälä, Vaara 15.10. Antti Korkealaakso 8 2 applications of portfolio decision analysis Grushka-Cockayne et al. (2008), Bryan (2010) model solution Hankimaa, Lundqvist 15.10. Suvi-Maria Laine 9 Nonadditive portfolio value functions Liesiö (2014) model solution Peltoketo, Vuola 22.10. Oliver Lundqvist 10 Decisionmaking under uncertainty: modeling alternatives, utility, utility functions, elicitation, incomplete information Eisenführ et al. 235-240, 251-255, 259-261, 291-302, Clemen (1996): 105-109, (465-477), MS-E2134 lecture material model solution Holopainen, Vilander 22.10. Johannes Mäkinen 11 Project portfolio selection under incomplete information of future scenarios and utility Liesiö and Salo (2012) model solution Anttila, Kontio 5.11. Matias Peltoketo 12 (Nonadditive) multiattribute utility functions for Portfolio Decision Analysis Liesiö and Vilkkumaa (2021) Avela, Holt 5.11. Mikko Rosenberg 13 Data Envelopment Analysis (DEA) methods with focus on CCR-DEA Cooper et al. (2006): 1-68, Charnes et al. (1978) Korkealaakso, Laine 12.11. Matti Staudinger 14 Preference information in DEA models: Value Efficiency Analysis (VEA) method + an application Halme et al. (1999), Korhonen et al. (2001) Vaara, Vuola 12.11. Viljami Uusihärkälä 15 Other DEA-models, cross efficiency concept Cooper et al. (2006): 83-110, Doyle and Green (1994) Lundqvist, Mäkinen 19.11. Lauri Vaara 16 REA method: Preference Programming in efficiency analysis Salo and Punkka (2011), Schang et al. (2016) Staudinger, Uusihärkälä, Hankimaa 19.11. Emilia Vuola 17 Modeling preference information with assurance regions Thompson et al. (1986) Peltoketo, Rosenberg, Holopainen