1. © K.Fedra 2000 1 Decision Support Systems an introduction to DSS with environmental application examples

2. © K.Fedra 2000 2 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

3. © K.Fedra 2000 3 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.

4. © K.Fedra 2000 4 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

5. © K.Fedra 2000 5 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

6. © K.Fedra 2000 6 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)

7. © K.Fedra 2000 7 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)

8. © K.Fedra 2000 8 Decision making processes (in the real world) are characterized by: multiple actorsmultiple actors conflicting objectivesconflicting objectives multiple criteriamultiple criteria plural rationalitiesplural rationalities hidden agendahidden agenda (in the real world) are characterized by: multiple actorsmultiple actors conflicting objectivesconflicting objectives multiple criteriamultiple criteria plural rationalitiesplural rationalities hidden agendahidden agenda

9. © K.Fedra 2000 9 Decision making processes are characterized by: multiple actorsmultiple actors conflicting objectivesconflicting objectives multiple criteriamultiple criteria plural rationalitiesplural rationalities hidden agendahidden agenda are characterized by: multiple actorsmultiple actors conflicting objectivesconflicting objectives multiple criteriamultiple criteria plural rationalitiesplural rationalities hidden agendahidden agenda

10. © K.Fedra 2000 10 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)

11. © K.Fedra 2000 11 Decision making processes are characterized by: multiple actorsmultiple actors conflicting objectivesconflicting objectives multiple criteriamultiple criteria plural rationalitiesplural rationalities hidden agendahidden agenda are characterized by: multiple actorsmultiple actors conflicting objectivesconflicting objectives multiple criteriamultiple criteria plural rationalitiesplural rationalities hidden agendahidden agenda

12. © K.Fedra 2000 12 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 generations 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 generations

13. © K.Fedra 2000 13 Decision making processes are characterized by: multiple actorsmultiple actors conflicting objectivesconflicting objectives multiple criteriamultiple criteria plural rationalitiesplural rationalities hidden agendahidden agenda are characterized by: multiple actorsmultiple actors conflicting objectivesconflicting objectives multiple criteriamultiple criteria plural rationalitiesplural rationalities hidden agendahidden agenda

14. © K.Fedra 2000 14 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)

15. © K.Fedra 2000 15 Decision making processes are characterized by: multiple actorsmultiple actors conflicting objectivesconflicting objectives multiple criteriamultiple criteria plural rationalitiesplural rationalities hidden agendahidden agenda are characterized by: multiple actorsmultiple actors conflicting objectivesconflicting objectives multiple criteriamultiple criteria plural rationalitiesplural rationalities hidden agendahidden agenda

16. © K.Fedra 2000 16 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.

17. © K.Fedra 2000 17 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.

18. © K.Fedra 2000 18 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.

19. © K.Fedra 2000 19 Decision making processes are characterized by: multiple actorsmultiple actors conflicting objectivesconflicting objectives multiple criteriamultiple criteria plural rationalitiesplural rationalities hidden agendahidden agenda are characterized by: multiple actorsmultiple actors conflicting objectivesconflicting objectives multiple criteriamultiple criteria plural rationalitiesplural rationalities hidden agendahidden agenda

20. © K.Fedra 2000 20 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

21. © K.Fedra 2000 21 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

22. © K.Fedra 2000 22 A general DSS architecture data acquisition layer graphical user interface analyticalenginemodelsexpertsystem DBMSGIS

23. © K.Fedra 2000 23 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

24. © K.Fedra 2000 24 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

25. © K.Fedra 2000 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 2000 26 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

27. © K.Fedra 2000 27 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

28. © K.Fedra 2000 28 User interface characteristics IntegrationIntegration InteractionInteraction VisualizationVisualization IntelligenceIntelligence CustomizationCustomization IntegrationIntegration InteractionInteraction VisualizationVisualization IntelligenceIntelligence CustomizationCustomization

29. © K.Fedra 2000 29 The User Interface provides integration of functionsprovides integration of functions interactive, dialogue oriented, menu driveninteractive, dialogue oriented, menu driven intuitive, graphical, symbolicintuitive, graphical, symbolic consistent syntax and semantics, layout and symbolismconsistent syntax and semantics, layout and symbolism intelligent, context awareintelligent, context aware customizedcustomized provides integration of functionsprovides integration of functions interactive, dialogue oriented, menu driveninteractive, dialogue oriented, menu driven intuitive, graphical, symbolicintuitive, graphical, symbolic consistent syntax and semantics, layout and symbolismconsistent syntax and semantics, layout and symbolism intelligent, context awareintelligent, context aware customizedcustomized

30. © K.Fedra 2000 30 The User Interface provides integration of functionsprovides integration of functions should provide access to ALL systems functions and resources.: seamless integration. seamless integration. For the non-technical user, the user interface IS the system. provides integration of functionsprovides integration of functions should provide access to ALL systems functions and resources.: seamless integration. seamless integration. For the non-technical user, the user interface IS the system.

31. © K.Fedra 2000 31 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

32. © K.Fedra 2000 32 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

33. © K.Fedra 2000 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 2000 34 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

35. © K.Fedra 2000 35 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.

36. © K.Fedra 2000 36 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

37. © K.Fedra 2000 37 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.

38. © K.Fedra 2000 38 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.

39. © K.Fedra 2000 39 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.

40. © K.Fedra 2000 40 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

41. © K.Fedra 2000 41 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)

42. © K.Fedra 2000 42 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 )

43. © K.Fedra 2000 43 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)

44. © K.Fedra 2000 44 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.

45. © K.Fedra 2000 45 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 ?

46. © K.Fedra 2000 46 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) u(45) < u(100, 0.5) ( u(0) = 0 ) u(45) < u(100, 0.5) ( u(0) = 0 ) u * (45) < u * (50) u * (45) < u * (50) 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) u(45) < u(100, 0.5) ( u(0) = 0 ) u(45) < u(100, 0.5) ( u(0) = 0 ) u * (45) < u * (50) u * (45) < u * (50)

47. © K.Fedra 2000 47 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 ?

48. © K.Fedra 2000 48 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 u(45) < u(100, 0.5, 0) u(45) < u(100, 0.5, 0) u * (45) < u * (50) u * (45) < u * (50) 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 u(45) < u(100, 0.5, 0) u(45) < u(100, 0.5, 0) u * (45) < u * (50) u * (45) < u * (50)

49. © K.Fedra 2000 49 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 ?

50. © K.Fedra 2000 50 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 u(100,0.05) > u(45,0.10) u(100,0.05) > u(45,0.10) u * (5) > u * (4.5) u * (5) > 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 u(100,0.05) > u(45,0.10) u(100,0.05) > u(45,0.10) u * (5) > u * (4.5) u * (5) > u * (4.5)

51. © K.Fedra 2000 51 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

52. © K.Fedra 2000 52 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

53. © K.Fedra 2000 53 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 ?

54. © K.Fedra 2000 54 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 !

55. © K.Fedra 2000 55 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 !

56. © K.Fedra 2000 56 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 ?

57. © K.Fedra 2000 57 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

58. © K.Fedra 2000 58 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

59. © K.Fedra 2000 59 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

60. © K.Fedra 2000 60 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

61. © K.Fedra 2000 61 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

62. © K.Fedra 2000 62 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