1. © K.Fedra 20004 1 Dimensions …… Mediterranean: Mediterranean: 3.7 10 6 km3 or 3.7 10 18 ltr Atomic weight of H 2 O = 18; 1 Mol of water = 18 g 1 ltr H 2 O = 55.5555 mol 1 mol = 6.022 10 23 molecules (Avogadro’s number) 1 ltr distributed in the Mediterranean Sea gives 3.35 10 7 molecules/ltr Mediterranean: Mediterranean: 3.7 10 6 km3 or 3.7 10 18 ltr Atomic weight of H 2 O = 18; 1 Mol of water = 18 g 1 ltr H 2 O = 55.5555 mol 1 mol = 6.022 10 23 molecules (Avogadro’s number) 1 ltr distributed in the Mediterranean Sea gives 3.35 10 7 molecules/ltr

2. © K.Fedra 20004 2 Decision Support Systems an introduction to DSS with environmental application examples

3. © K.Fedra 20004 3 What is a DSS ? Attempts at definitionAttempts at definition Decision making processesDecision making processes A general DSS architectureA general DSS architecture Decision Support ParadigmsDecision Support Paradigms Application examplesApplication examples Attempts at definitionAttempts at definition Decision making processesDecision making processes A general DSS architectureA general DSS architecture Decision Support ParadigmsDecision Support Paradigms Application examplesApplication examples

4. © K.Fedra 20004 4 DSS Definition A DSS is a computer based problem solving system that assists choice between alternatives in complex and controversial domains. A DSS is a computer based problem solving system that assists choice between alternatives in complex and controversial domains.

5. © K.Fedra 20004 5 DSS Definition Problem solving: Problem: when the observed or perceived (expected) state of a system differs from the expectations, norms, goals. If the expectation is optimisation (maximisation, growth) we always have a problem (more than yesterday, more than others) Problem solving: Problem: when the observed or perceived (expected) state of a system differs from the expectations, norms, goals. If the expectation is optimisation (maximisation, growth) we always have a problem (more than yesterday, more than others)

6. © K.Fedra 20004 6 DSS Definition A DSS provides A DSS provides structured presentationstructured presentation problem context,problem context, and tools for theand tools for the – design, – evaluation, – selection of alternatives A DSS provides A DSS provides structured presentationstructured presentation problem context,problem context, and tools for theand tools for the – design, – evaluation, – selection of alternatives

7. © K.Fedra 20004 7 What is a DSS ? Attempts at definitionAttempts at definition Decision making processesDecision making processes A general DSS architectureA general DSS architecture Decision Support ParadigmsDecision Support Paradigms Application examplesApplication examples Attempts at definitionAttempts at definition Decision making processesDecision making processes A general DSS architectureA general DSS architecture Decision Support ParadigmsDecision Support Paradigms Application examplesApplication examples

8. © K.Fedra 20004 8 Decision making processes Handbook of OR (B.E.Gillet, 1976): Formulation of the problemFormulation of the problem Construction of a mathematical modelConstruction of a mathematical model Derive solution from modelDerive solution from model Testing model and solutionTesting model and solution Establish control over the solutionEstablish control over the solution Put it to work (implementation)Put it to work (implementation) Handbook of OR (B.E.Gillet, 1976): Formulation of the problemFormulation of the problem Construction of a mathematical modelConstruction of a mathematical model Derive solution from modelDerive solution from model Testing model and solutionTesting model and solution Establish control over the solutionEstablish control over the solution Put it to work (implementation)Put it to work (implementation)

9. © K.Fedra 20004 9 Decision making processes Heuristics (How to solve it, G.Polya) understand the problemunderstand the problem make a plan (algorithm)make a plan (algorithm) implement step by stepimplement step by step check each stepcheck each step check the solution (looking back)check the solution (looking back) Heuristics (How to solve it, G.Polya) understand the problemunderstand the problem make a plan (algorithm)make a plan (algorithm) implement step by stepimplement step by step check each stepcheck each step check the solution (looking back)check the solution (looking back)

10. © K.Fedra 20004 10 Decision making processes (in the real world) are characterized by: multiple actorsmultiple actors uncertaintyuncertainty conflicting objectivesconflicting objectives multiple criteriamultiple criteria plural rationalitiesplural rationalities hidden agendahidden agenda (in the real world) are characterized by: multiple actorsmultiple actors uncertaintyuncertainty conflicting objectivesconflicting objectives multiple criteriamultiple criteria plural rationalitiesplural rationalities hidden agendahidden agenda

11. © K.Fedra 20004 11 Decision making processes are characterized by: multiple actorsmultiple actors uncertaintyuncertainty conflicting objectivesconflicting objectives multiple criteriamultiple criteria plural rationalitiesplural rationalities hidden agendahidden agenda are characterized by: multiple actorsmultiple actors uncertaintyuncertainty conflicting objectivesconflicting objectives multiple criteriamultiple criteria plural rationalitiesplural rationalities hidden agendahidden agenda

12. © K.Fedra 20004 12 Decision making processes multiple actors: researchers and analysts researchers and analysts planners and managers planners and managers policy and decision makers policy and decision makers general public: general public: consumers (market) consumers (market) concerned citizen (voters) concerned citizen (voters) researchers and analysts researchers and analysts planners and managers planners and managers policy and decision makers policy and decision makers general public: general public: consumers (market) consumers (market) concerned citizen (voters) concerned citizen (voters)

13. © K.Fedra 20004 13 Decision making processes are characterized by: multiple actorsmultiple actors uncertaintyuncertainty conflicting objectivesconflicting objectives multiple criteriamultiple criteria plural rationalitiesplural rationalities hidden agendahidden agenda are characterized by: multiple actorsmultiple actors uncertaintyuncertainty conflicting objectivesconflicting objectives multiple criteriamultiple criteria plural rationalitiesplural rationalities hidden agendahidden agenda

14. © K.Fedra 20004 14 Decision making processes Uncertainty: All elements are “uncertain”: Criteria,Criteria, Objectives,Objectives, ConstraintsConstraintsUncertainty: All elements are “uncertain”: Criteria,Criteria, Objectives,Objectives, ConstraintsConstraints

15. © K.Fedra 20004 15 Decision making processes are characterized by: multiple actorsmultiple actors uncertaintyuncertainty conflicting objectivesconflicting objectives multiple criteriamultiple criteria plural rationalitiesplural rationalities hidden agendahidden agenda are characterized by: multiple actorsmultiple actors uncertaintyuncertainty conflicting objectivesconflicting objectives multiple criteriamultiple criteria plural rationalitiesplural rationalities hidden agendahidden agenda

16. © K.Fedra 20004 16 Decision making processes conflicting objectives: maximize economic benefits maximize economic benefits minimize environmental costs minimize environmental costs maximize environmental benefits maximize environmental benefits minimize economic costs minimize economic costs maintain equity: maintain equity: between social groups between social groups between regions and countries between regions and countries between generations between generationsSUSTAINABILITY maximize economic benefits maximize economic benefits minimize environmental costs minimize environmental costs maximize environmental benefits maximize environmental benefits minimize economic costs minimize economic costs maintain equity: maintain equity: between social groups between social groups between regions and countries between regions and countries between generations between generationsSUSTAINABILITY

17. © K.Fedra 20004 17 Decision making processes are characterized by: multiple actorsmultiple actors uncertaintyuncertainty conflicting objectivesconflicting objectives multiple criteriamultiple criteria plural rationalitiesplural rationalities hidden agendahidden agenda are characterized by: multiple actorsmultiple actors uncertaintyuncertainty conflicting objectivesconflicting objectives multiple criteriamultiple criteria plural rationalitiesplural rationalities hidden agendahidden agenda

18. © K.Fedra 20004 18 Decision making processes multiple criteria: economic criteria (costs) economic criteria (costs) environmental criteria environmental criteria standards (measurements) standards (measurements) perceptions (believes, fears) perceptions (believes, fears) political criteria (equity) political criteria (equity) regulatory criteria (constraints) regulatory criteria (constraints) technological criteria (constraints) technological criteria (constraints) economic criteria (costs) economic criteria (costs) environmental criteria environmental criteria standards (measurements) standards (measurements) perceptions (believes, fears) perceptions (believes, fears) political criteria (equity) political criteria (equity) regulatory criteria (constraints) regulatory criteria (constraints) technological criteria (constraints) technological criteria (constraints)

19. © K.Fedra 20004 19 Decision making processes are characterized by: multiple actorsmultiple actors uncertaintyuncertainty conflicting objectivesconflicting objectives multiple criteriamultiple criteria plural rationalitiesplural rationalities hidden agendahidden agenda are characterized by: multiple actorsmultiple actors uncertaintyuncertainty conflicting objectivesconflicting objectives multiple criteriamultiple criteria plural rationalitiesplural rationalities hidden agendahidden agenda

20. © K.Fedra 20004 20 Decision making processes plural rationalities rational: relating to, based on, agreeable to reason. reason: the power of inferring, comprehending, or thinking in an orderly, rational way. plural rationalities rational: relating to, based on, agreeable to reason. reason: the power of inferring, comprehending, or thinking in an orderly, rational way.

21. © K.Fedra 20004 21 Decision making processes plural rationalities rational: L. ratio (reor, reri, ratus) computation, advantage, interest, behavior, procedure, ways and means, motivation, argument, proof, opinion, (scientific) theory. plural rationalities rational: L. ratio (reor, reri, ratus) computation, advantage, interest, behavior, procedure, ways and means, motivation, argument, proof, opinion, (scientific) theory.

22. © K.Fedra 20004 22 Decision making processes plural rationalities reaching different (contradictory) conclusions from the same set of premises in an internally consistent logical way. plural rationalities reaching different (contradictory) conclusions from the same set of premises in an internally consistent logical way.

23. © K.Fedra 20004 23 Decision making processes are characterized by: multiple actorsmultiple actors uncertaintyuncertainty conflicting objectivesconflicting objectives multiple criteriamultiple criteria plural rationalitiesplural rationalities hidden agendahidden agenda are characterized by: multiple actorsmultiple actors uncertaintyuncertainty conflicting objectivesconflicting objectives multiple criteriamultiple criteria plural rationalitiesplural rationalities hidden agendahidden agenda

24. © K.Fedra 20004 24 Decision making processes Hidden agenda: Not all objectives of all actors are disclosed. Proclaim one (popular) objective to reach another, different (and not disclosed, less popular or acceptable) objective. Hidden agenda: Not all objectives of all actors are disclosed. Proclaim one (popular) objective to reach another, different (and not disclosed, less popular or acceptable) objective.

25. © K.Fedra 20004 25 A general DSS architecture Information resourcesInformation resources The analytical engineThe analytical engine The user interfaceThe user interface Information resourcesInformation resources The analytical engineThe analytical engine The user interfaceThe user interface

26. © K.Fedra 20004 26 Information Resources information on the status-quo (monitoring)information on the status-quo (monitoring) background for thebackground for the identification or design identification or design of decision alternatives of decision alternatives information on the status-quo (monitoring)information on the status-quo (monitoring) background for thebackground for the identification or design identification or design of decision alternatives of decision alternatives

27. © K.Fedra 20004 27 The analytical engine Data base management systemData base management system Geographic Information SystemGeographic Information System Simulation and optimization modelsSimulation and optimization models Expert systems (rules)Expert systems (rules) Decision Support tools properDecision Support tools proper Data base management systemData base management system Geographic Information SystemGeographic Information System Simulation and optimization modelsSimulation and optimization models Expert systems (rules)Expert systems (rules) Decision Support tools properDecision Support tools proper

28. © K.Fedra 20004 28 The User Interface interactive, dialogue oriented, menu driven, intuitive, graphical, symbolicinteractive, dialogue oriented, menu driven, intuitive, graphical, symbolic consistent syntax and semantics, layout and symbolism, intelligent, context aware, customizedconsistent syntax and semantics, layout and symbolism, intelligent, context aware, customized also includes organizational issues (e.g., for workshops, presentations, hearings) group dynamics, communicationalso includes organizational issues (e.g., for workshops, presentations, hearings) group dynamics, communication ALL SCIENCE IS PROPAGANDA (P.Feyerabend) interactive, dialogue oriented, menu driven, intuitive, graphical, symbolicinteractive, dialogue oriented, menu driven, intuitive, graphical, symbolic consistent syntax and semantics, layout and symbolism, intelligent, context aware, customizedconsistent syntax and semantics, layout and symbolism, intelligent, context aware, customized also includes organizational issues (e.g., for workshops, presentations, hearings) group dynamics, communicationalso includes organizational issues (e.g., for workshops, presentations, hearings) group dynamics, communication ALL SCIENCE IS PROPAGANDA (P.Feyerabend)

29. © K.Fedra 20004 29 Decision support paradigms Information systems Scenario analysis Scenario analysis WHAT IF WHAT IF Rational maximization Rational maximization HOW TO HOW TO Multiple attributes Multiple attributes Information systems Scenario analysis Scenario analysis WHAT IF WHAT IF Rational maximization Rational maximization HOW TO HOW TO Multiple attributes Multiple attributes

30. © K.Fedra 20004 30 Decision support paradigms Information systems Scenario analysis Scenario analysis WHAT IF WHAT IF Rational maximization Rational maximization HOW TO HOW TO Multiple attributes Multiple attributes Information systems Scenario analysis Scenario analysis WHAT IF WHAT IF Rational maximization Rational maximization HOW TO HOW TO Multiple attributes Multiple attributes

31. © K.Fedra 20004 31 Information systems provide problem contextprovide problem context describe available alternativesdescribe available alternatives offer a common language and shared information basis for the participants in the decision making processoffer a common language and shared information basis for the participants in the decision making process provide problem contextprovide problem context describe available alternativesdescribe available alternatives offer a common language and shared information basis for the participants in the decision making processoffer a common language and shared information basis for the participants in the decision making process

32. © K.Fedra 20004 32 Information systems typical application example: State-of-the-Environment Reporting decision process usually diffuse, multi-stage and lengthy without clear technical objectives. Public information, awareness building, assists argumentation. typical application example: State-of-the-Environment Reporting decision process usually diffuse, multi-stage and lengthy without clear technical objectives. Public information, awareness building, assists argumentation.

33. © K.Fedra 20004 33 Decision support paradigms Information systems Scenario analysis Scenario analysis WHAT IF WHAT IF Rational maximization Rational maximization HOW TO HOW TO Multiple attributes Multiple attributes Information systems Scenario analysis Scenario analysis WHAT IF WHAT IF Rational maximization Rational maximization HOW TO HOW TO Multiple attributes Multiple attributes

34. © K.Fedra 20004 34 Decision support paradigms Scenario analysis explores the reaction of a system to changes in the control or decision variables on the performance variables (criteria) in terms of the objectives and constraints of the decision problem. Scenario analysis explores the reaction of a system to changes in the control or decision variables on the performance variables (criteria) in terms of the objectives and constraints of the decision problem.

35. © K.Fedra 20004 35 Decision support paradigms Scenario from L. scaenarium, the stage an account or synopsis of a projected course of action or events; a set of assumptions. Scenario from L. scaenarium, the stage an account or synopsis of a projected course of action or events; a set of assumptions.

36. © K.Fedra 20004 36 Decision support paradigms typical application example: Environmental Impact Assessment, that evaluates and compares project alternatives. Exploratory (policy) assessment, design of alternatives. typical application example: Environmental Impact Assessment, that evaluates and compares project alternatives. Exploratory (policy) assessment, design of alternatives.

37. © K.Fedra 20004 37 Decision support paradigms Information systems Scenario analysis Scenario analysis WHAT IF WHAT IF Rational maximization Rational maximization HOW TO HOW TO Multiple attributes Multiple attributes Information systems Scenario analysis Scenario analysis WHAT IF WHAT IF Rational maximization Rational maximization HOW TO HOW TO Multiple attributes Multiple attributes

38. © K.Fedra 20004 38 Rational maximization The individual as rational maximizer chooses a commodity bundle chooses a commodity bundle c = (c 1,...,c i,...,c n ) c = (c 1,...,c i,...,c n ) that maximizes the utility that maximizes the utility u(c) u(c) The individual as rational maximizer chooses a commodity bundle chooses a commodity bundle c = (c 1,...,c i,...,c n ) c = (c 1,...,c i,...,c n ) that maximizes the utility that maximizes the utility u(c) u(c)

39. © K.Fedra 20004 39 Rational maximization maximize the utility u(c) – over different groups ( i ) – over space (x,y,z) – over time ( t ) maximize the utility u(c) – over different groups ( i ) – over space (x,y,z) – over time ( t )

40. © K.Fedra 20004 40 Rational maximization The social welfare function u*(c) = f [u 1 (c),u 2 (c),...,u n (c) ] u*(c) = f [u 1 (c),u 2 (c),...,u n (c) ] as the sum as the sum  i u i (c)  i u i (c) of individual or group of individual or group utility functions u i (c) utility functions u i (c) The social welfare function u*(c) = f [u 1 (c),u 2 (c),...,u n (c) ] u*(c) = f [u 1 (c),u 2 (c),...,u n (c) ] as the sum as the sum  i u i (c)  i u i (c) of individual or group of individual or group utility functions u i (c) utility functions u i (c)

41. © K.Fedra 20004 41 Rational choice Let (x,p,y) denote an option where x is obtained with probability p x is obtained with probability p y is obtained with probability 1-p y is obtained with probability 1-p from: A.Tversky, (1977) from: A.Tversky, (1977) On the elicitation of preferences On the elicitation of preferences. Let (x,p,y) denote an option where x is obtained with probability p x is obtained with probability p y is obtained with probability 1-p y is obtained with probability 1-p from: A.Tversky, (1977) from: A.Tversky, (1977) On the elicitation of preferences On the elicitation of preferences.

42. © K.Fedra 20004 42 Rational choice Assume two alternatives of emergency management: emergency management: A 1 50:50 to lose 100 lives A 1 50:50 to lose 100 lives A 2 certain to lose 45 lives A 2 certain to lose 45 lives You can execute A 1 OR A 2 You can execute A 1 OR A 2 What do you choose ? What do you choose ? Assume two alternatives of emergency management: emergency management: A 1 50:50 to lose 100 lives A 1 50:50 to lose 100 lives A 2 certain to lose 45 lives A 2 certain to lose 45 lives You can execute A 1 OR A 2 You can execute A 1 OR A 2 What do you choose ? What do you choose ?

43. © K.Fedra 20004 43 Rational choice A 1 50:50 to lose 100 lives (100, 1/2, 0) (100, 1/2, 0) A 2 certain to lose 45 lives (45) (45) A 1 50:50 to lose 100 lives (100, 1/2, 0) (100, 1/2, 0) A 2 certain to lose 45 lives (45) (45)

44. © K.Fedra 20004 44 Rational choice Assume two alternatives of health programs: health programs: A 1 50:50 to save 100 lives A 1 50:50 to save 100 lives A 2 certain to save 45 lives A 2 certain to save 45 lives You can implement A 1 OR A 2 You can implement A 1 OR A 2 What do you choose ? What do you choose ? Assume two alternatives of health programs: health programs: A 1 50:50 to save 100 lives A 1 50:50 to save 100 lives A 2 certain to save 45 lives A 2 certain to save 45 lives You can implement A 1 OR A 2 You can implement A 1 OR A 2 What do you choose ? What do you choose ?

45. © K.Fedra 20004 45 Rational choice A 1 1:2 to save 100 lives (100, 0.5, 0) u * = 50 (100, 0.5, 0) u * = 50 A 2 certain to save 45 lives ( 45) u * = 45 ( 45) u * = 45 A 1 1:2 to save 100 lives (100, 0.5, 0) u * = 50 (100, 0.5, 0) u * = 50 A 2 certain to save 45 lives ( 45) u * = 45 ( 45) u * = 45

46. © K.Fedra 20004 46 Rational choice Assume two alternatives of health programs: health programs: A 1 1:20 to save 100 lives A 1 1:20 to save 100 lives A 2 1:10 to save 45 lives A 2 1:10 to save 45 lives You can implement A 1 OR A 2 You can implement A 1 OR A 2 What do you choose ? What do you choose ? Assume two alternatives of health programs: health programs: A 1 1:20 to save 100 lives A 1 1:20 to save 100 lives A 2 1:10 to save 45 lives A 2 1:10 to save 45 lives You can implement A 1 OR A 2 You can implement A 1 OR A 2 What do you choose ? What do you choose ?

47. © K.Fedra 20004 47 Rational choice A 1 1:20 to save 100 lives (100, 0.05, 0) u * = 5 (100, 0.05, 0) u * = 5 A 2 1:10 to save 45 lives ( 45, 0.10, 0) u * = 4.5 ( 45, 0.10, 0) u * = 4.5 A 1 1:20 to save 100 lives (100, 0.05, 0) u * = 5 (100, 0.05, 0) u * = 5 A 2 1:10 to save 45 lives ( 45, 0.10, 0) u * = 4.5 ( 45, 0.10, 0) u * = 4.5

48. © K.Fedra 20004 48 Rational choice context dependence and bias: certainty versus probability certainty versus probability gain versus loss gain versus loss absolute versus relative change absolute versus relative change context dependence and bias: certainty versus probability certainty versus probability gain versus loss gain versus loss absolute versus relative change absolute versus relative change

49. © K.Fedra 20004 49 Decision making Minimax and Bayesian approaches: Decision maker has: a finite number of possible decision alternativesa finite number of possible decision alternatives a finite number of outcomes (state of nature) which may have a known probability of outcomea finite number of outcomes (state of nature) which may have a known probability of outcome a cost or benefit for each decision - state-of- nature combinationa cost or benefit for each decision - state-of- nature combination Minimax and Bayesian approaches: Decision maker has: a finite number of possible decision alternativesa finite number of possible decision alternatives a finite number of outcomes (state of nature) which may have a known probability of outcomea finite number of outcomes (state of nature) which may have a known probability of outcome a cost or benefit for each decision - state-of- nature combinationa cost or benefit for each decision - state-of- nature combination

50. © K.Fedra 20004 50 Decision making Decision Table: State of Nature State of Nature Decisionrain no-rain take a raincoat 0 3 no raincoat 6 0 (0, 3, 6, are the associated costs) What do you do ? Decision Table: State of Nature State of Nature Decisionrain no-rain take a raincoat 0 3 no raincoat 6 0 (0, 3, 6, are the associated costs) What do you do ?

51. © K.Fedra 20004 51 Decision making Decision Table: State of Nature State of Nature Decisionrain no-rain take a raincoat 0 3(3) no raincoat 6 0(6) Minimax Solution (conservative): take a raincoat ! Decision Table: State of Nature State of Nature Decisionrain no-rain take a raincoat 0 3(3) no raincoat 6 0(6) Minimax Solution (conservative): take a raincoat !

52. © K.Fedra 20004 52 Decision making Decision Table: (with added probabilities) State of Nature State of Nature Decisionrain (0.1) no-rain (0.9) take a raincoat 0 (0) 3(2.7)(2.7) no raincoat 6 (0.6) 0 (0)(0.6) Bayesian Solution: don’t take a raincoat ! Decision Table: (with added probabilities) State of Nature State of Nature Decisionrain (0.1) no-rain (0.9) take a raincoat 0 (0) 3(2.7)(2.7) no raincoat 6 (0.6) 0 (0)(0.6) Bayesian Solution: don’t take a raincoat !

53. © K.Fedra 20004 53 Decision making Decision Table: States of Nature States of Nature Decision rain (0.1) little (0.5) none (0.4) take a raincoat 0 (0) 0 (0) 3 (1.2) no raincoat 6 (0.6) 1 (0.5) 0 (0) And now ? Decision Table: States of Nature States of Nature Decision rain (0.1) little (0.5) none (0.4) take a raincoat 0 (0) 0 (0) 3 (1.2) no raincoat 6 (0.6) 1 (0.5) 0 (0) And now ?

54. © K.Fedra 20004 54 Decision making Decision Table: States of Nature States of Nature Decision rain (0.1) little (0.5) none (0.4) take a raincoat 0 (0) 0 (0) 3 (1.2) 1.2 no raincoat 6 (0.6) 1 (0.5) 0 (0) 1.1 MiniMax: take a raincoat Bayesian:take no raincoat Decision Table: States of Nature States of Nature Decision rain (0.1) little (0.5) none (0.4) take a raincoat 0 (0) 0 (0) 3 (1.2) 1.2 no raincoat 6 (0.6) 1 (0.5) 0 (0) 1.1 MiniMax: take a raincoat Bayesian:take no raincoat

55. © K.Fedra 20004 55 Decision support paradigms Information systems Scenario analysis Scenario analysis WHAT IF WHAT IF Rational maximization Rational maximization HOW TO HOW TO Multiple attributes Multiple attributes Information systems Scenario analysis Scenario analysis WHAT IF WHAT IF Rational maximization Rational maximization HOW TO HOW TO Multiple attributes Multiple attributes

56. © K.Fedra 20004 56 Decision support paradigms Multiple attributes multiple objectives multiple objectives multiple criteria multiple criteria trade-off, compromise, trade-off, compromise, satisfaction, acceptance satisfaction, acceptance Multiple attributes multiple objectives multiple objectives multiple criteria multiple criteria trade-off, compromise, trade-off, compromise, satisfaction, acceptance satisfaction, acceptance

57. © K.Fedra 20004 57 Decision making process Problem descriptionProblem description Set of criteriaSet of criteria – objectives – constraints Set of feasible alternativesSet of feasible alternatives Evaluation of alternativesEvaluation of alternatives Decision rulesDecision rules Problem descriptionProblem description Set of criteriaSet of criteria – objectives – constraints Set of feasible alternativesSet of feasible alternatives Evaluation of alternativesEvaluation of alternatives Decision rulesDecision rules

58. © K.Fedra 20004 58 Decision making process Spatial decisions: Set of criteriaSet of criteria – objectives – constraints are functions of space are functions of space Spatial decisions: Set of criteriaSet of criteria – objectives – constraints are functions of space are functions of space

59. © K.Fedra 20004 59 Spatial decisions Environmental decision are also spatial decisions: site selection, locationsite selection, location pollution controlpollution control natural resources managementnatural resources management environmental impact assessmentenvironmental impact assessment risk analysis and managementrisk analysis and management Environmental decision are also spatial decisions: site selection, locationsite selection, location pollution controlpollution control natural resources managementnatural resources management environmental impact assessmentenvironmental impact assessment risk analysis and managementrisk analysis and management