62
R. Bruggemann and L. Carlsen
Carlsen, L., & Bruggemann, R..(2011). Decision support tools in environmental forensics.
In Organizing Committee of the “Experts Workshop” on Environmental Forensics (Ed.),
Environmental forensics (pp. 239–247). #, Tbilisi, Georgia.
Carlsen, L., & Bruggemann, R. (2014). Indicator analyses: What is important – And for what? In
R. Bruggemann, L. Carlsen, & J. Wittmann (Eds.), Multi-indicator systems and modelling in
partial order (pp. 359–387). New York: Springer.
Colorni, A., Paruccini, M., & Roy, B. (2001). A-MCD-A, Aide Multi Critere a la Decision, Multiple
Criteria Decision Aiding. Ispra: JRC European Commission.
Figueira, J., Greco, S., & Ehrgott, M. (2005). Multiple criteria decision analysis, state of the art
surveys. Boston: Springer.
Hasse, H. (1967). Vorlesungen über Klassenkörpertheorie. Marburg: Physica-Verlag.
Helm, D. (2006). Evaluation of biomonitoring data. In R. Bruggemann & L. Carlsen (Eds.), Partial
order in environmental sciences and chemistry (pp. 285–307). Berlin: Springer.
Munda, G. (2008). Social multi-criteria evaluation for a sustainable economy. Berlin: Springer.
Munda, G., & Nardo, M. (2008). Noncompensatory/nonlinear composite indicators for ranking
countries: A defensible setting. Applied Economics, 41, 1–11.
Nardo, M. (2008). Handbook on constructing composite indicators -methodology and user guide.
Ispra: OECD.
Newlin, J., & Patil, G. P. (2010). Application of partial order to stream channel assessment at
bridge infrastructure for mitigation management. Environmental and Ecological Statistics, 17,
437–454.
Patil, G. P., & Taillie, C. (2004). Multiple indicators, partially ordered sets, and linear extensions:
Multi-criterion ranking and prioritization. Environmental and Ecological Statistics, 11, 199–
228.
Roy, B. (1972). Electre III: Un Algorithme de Classements fonde sur une representation floue
des Preferences En Presence de Criteres Multiples. Cahiers du Centre d’Etudes de Recherche
Operationelle, 20, 32–43.
Roy, B. (1990). The outranking approach and the foundations of the ELECTRE methods. In C. A.
Bana e Costa (Ed.), Readings in multiple criteria decision aid (pp. 155–183). Berlin: Springer.
Simon, U., Bruggemann, R., Pudenz, S., & Behrendt, H. (2006). Aspects of decision support in
water management: Data based evaluation compared with expectations. In R. Bruggemann &
L. Carlsen (Eds.), Partial order in environmental sciences and chemistry (pp. 221–236). Berlin:
Springer.
Sørensen, P. B., Lerche, D., & Thomsen, M. (2006). Developing decision support based on
field data and partial order theory. In R. Bruggemann & L. Carlsen (Eds.), Partial order in
environmental sciences and chemistry (pp. 260–283). Berlin: Springer.
UNICEF, Innocenti Research Centre, Report card 7, 2007.
Wieland, R., & Bruggemann, R. (2013). Hasse diagram technique and Monte Carlo simulations.
MATCH Communications in Mathematical and in Computer Chemistry, 70, 45–59.
R. Bruggemann and L. Carlsen
Carlsen, L., & Bruggemann, R..(2011). Decision support tools in environmental forensics.
In Organizing Committee of the “Experts Workshop” on Environmental Forensics (Ed.),
Environmental forensics (pp. 239–247). #, Tbilisi, Georgia.
Carlsen, L., & Bruggemann, R. (2014). Indicator analyses: What is important – And for what? In
R. Bruggemann, L. Carlsen, & J. Wittmann (Eds.), Multi-indicator systems and modelling in
partial order (pp. 359–387). New York: Springer.
Colorni, A., Paruccini, M., & Roy, B. (2001). A-MCD-A, Aide Multi Critere a la Decision, Multiple
Criteria Decision Aiding. Ispra: JRC European Commission.
Figueira, J., Greco, S., & Ehrgott, M. (2005). Multiple criteria decision analysis, state of the art
surveys. Boston: Springer.
Hasse, H. (1967). Vorlesungen über Klassenkörpertheorie. Marburg: Physica-Verlag.
Helm, D. (2006). Evaluation of biomonitoring data. In R. Bruggemann & L. Carlsen (Eds.), Partial
order in environmental sciences and chemistry (pp. 285–307). Berlin: Springer.
Munda, G. (2008). Social multi-criteria evaluation for a sustainable economy. Berlin: Springer.
Munda, G., & Nardo, M. (2008). Noncompensatory/nonlinear composite indicators for ranking
countries: A defensible setting. Applied Economics, 41, 1–11.
Nardo, M. (2008). Handbook on constructing composite indicators -methodology and user guide.
Ispra: OECD.
Newlin, J., & Patil, G. P. (2010). Application of partial order to stream channel assessment at
bridge infrastructure for mitigation management. Environmental and Ecological Statistics, 17,
437–454.
Patil, G. P., & Taillie, C. (2004). Multiple indicators, partially ordered sets, and linear extensions:
Multi-criterion ranking and prioritization. Environmental and Ecological Statistics, 11, 199–
228.
Roy, B. (1972). Electre III: Un Algorithme de Classements fonde sur une representation floue
des Preferences En Presence de Criteres Multiples. Cahiers du Centre d’Etudes de Recherche
Operationelle, 20, 32–43.
Roy, B. (1990). The outranking approach and the foundations of the ELECTRE methods. In C. A.
Bana e Costa (Ed.), Readings in multiple criteria decision aid (pp. 155–183). Berlin: Springer.
Simon, U., Bruggemann, R., Pudenz, S., & Behrendt, H. (2006). Aspects of decision support in
water management: Data based evaluation compared with expectations. In R. Bruggemann &
L. Carlsen (Eds.), Partial order in environmental sciences and chemistry (pp. 221–236). Berlin:
Springer.
Sørensen, P. B., Lerche, D., & Thomsen, M. (2006). Developing decision support based on
field data and partial order theory. In R. Bruggemann & L. Carlsen (Eds.), Partial order in
environmental sciences and chemistry (pp. 260–283). Berlin: Springer.
UNICEF, Innocenti Research Centre, Report card 7, 2007.
Wieland, R., & Bruggemann, R. (2013). Hasse diagram technique and Monte Carlo simulations.
MATCH Communications in Mathematical and in Computer Chemistry, 70, 45–59.