Making decisions in planning has three prominent characteristics: multicriteria, multiparticipants, and fuzziness. A model that deals with these three properties simultaneously is presented as a promising tool for land-use planning, and its potential usefulness in group decisionmaking and for building expert systems is discussed.
Get full access to this article
View all access options for this article.
References
1.
• Papers of particular interest which are not cited in the text.
2.
ArrowK J, 1951Social Choice and Individual Values. Cowles Commission Monograph 12 (John Wiley, New York)
3.
BellmanR EZadehL A, 1970, “Decision making in a fuzzy environment”Management Science17B141–B164
BlinJ M, 1974, “Fuzzy relations in group decision theory”Journal of Cybernetics4(2) 17–22
6.
BlinJ MWhinstonA B, 1973, “Fuzzy sets and social choice”Journal of Cybernetics3(4) 28–36
7.
BodilyS E, 1979, “A delegation process for combining individual utility functions”Management Science251035–1041
8.
BuchananA, 1985Ethics, Efficiency and the Market (Rowman and Allanheld, Totowa, NJ)
9.
DalkeyN C, 1969The Delphi Method: An Experimental Study of Group Opinion (The Rand Corporation, Santa Monica, CA)
10.
DalkeyN CBrownB, 1971Comparison of Group Judgment Techniques with Short-range Predictions and Almanac Questions (The Rand Corporation, Santa Monica, CA)
11.
DalkeyN CRourkeD L, 1971Experimental Assessment of Delphi Procedures with Group Value Judgments (The Rand Corporation, Santa Monica, CA)
12.
• Damon Road Task Force, 1985, “Final report of the Damon Road Task Force”, unpublished, Northampton Department of Public Works, 210 Main Street, Northampton, MA 01060
13.
DavisR, 1984, “Amplifying expertise with expert systems”, in The AI Business: The Commercial Uses of Artificial Intelligence Ed. WinstonP HPendergastK A (MIT Press, Cambridge, MA) pp 17–40
14.
DuboisDPradeH, 1980Fuzzy Sets and Systems: Theory and Applications (Academic Press, New York)
15.
FungL WFuK S, 1975, “An axiomatic approach to rational decision making in a fuzzy environment”, in Fuzzy Sets and Their Applications to Cognitive and Decision Processes Eds ZadehL AFuK STanakaKShimuraM (Academic Press, New York) pp 227–256
16.
GainesB R, 1983, “Precise past—fuzzy future”International Journal of Man-Machine Studies19117–134
17.
GoicoecheaAHansenD RDuckstemL, 1982Multiobjective Decision Analysis With Engineering and Business Applications (John Wiley, New York) pp 336–343
18.
GuptaM M, 1985, “Preface”, in Approximate Reasoning in Expert Systems Eds GuptaM MKandelABandlerWKiszkaJ B (North-Holland, Amsterdam) pp ix–xi
HipelK W, 1982, “Fuzzy set methodologies in multicriteria modelling”, in Fuzzy Information and Decision Processes Eds GuptaM MSanchezE (North-Holland, Amsterdam) pp 279–287
21.
KeeneyR L, 1976, “A group preference axiomatization with cardinal utility”Management Science23140–145
22.
KeeneyR LKirkwoodC W, 1975, “Group decision making using cardinal social welfare functions”Management Science22430–437
23.
KeeneyR LRaiffaH, 1976Decisions With Multiple Objectives (John Wiley, New York)
24.
KirkwoodC W, 1972, “Decision analysis incorporating preferences of groups”, TR47, Operations Research Center, Massachusetts Institute of Technology, Cambridge, MA
25.
KirkwoodC W, 1974, “Group decision making under forced uncertainty”, TR 74–5, Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI
26.
van LemkeH R NDijkmanT Gvan HaeringenHPleegingM, 1983, “A characteristic optimism factor in fuzzy decision-making”, in Fuzzy Information, Knowledge Representation and Decision Analysis Ed. SanchezE (Pergamon Press, Oxford) pp 283–288
27.
MacDougallE B, 1981, “Fuzzy set evaluation in landscape assessment”, paper presented at the 1981 Annual Meeting of American Society of Landscape Architects; copy available from Department of Landscape Architecture and Regional Planning, University of Massachusetts, Amherst, MA
28.
• SenA K, 1970Collective Choice and Social Welfare (Holden-Day, San Francisco, CA)
29.
SobralM MHipelK WFarquharG J, 1981, “A multicriteria model for solid waste management”Journal of Environmental Management1297–110
30.
WallisW ARobertsH W, 1964Statistics: A New Approach (Free Press, New York)
31.
WerczbergerE, 1983, “Multiperson multitarget decision making, using the versatility criterion”Regional Science and Urban Economics13103–113
32.
WinstonP H, 1984, “Perspective”, in The AI Business: The Commercial Uses of Artificial Intelligence Eds WinstonP HPendergastK A (MIT Press, Cambridge, MA) pp 1–13
33.
YagerR R, 1977, “Multiple objective decision-making using fuzzy sets”International Journal of Man-Machine Studies9375–382
34.
YagerR R, 1978, “Fuzzy decision making including unequal objectives”Fuzzy Sets and Systems187–95
35.
YagerR R, 1981, “A new methodology for ordinal multiobjective decisions based on fuzzy sets”Decision Sciences12589–600
36.
• YagerR RBassonD, 1975, “Decision making with fuzzy sets”Decision Sciences6590–600
37.
ZadehL A, 1965, “Fuzzy sets”Information Control8338–353
38.
ZadehL A, 1973, “Outline of a new approach to the analysis of complex systems and decision processes”IEEE Transactions on Systems, Man and Cybernetics328–44
39.
ZadehL A, 1982, “Foreword”, in Fuzzy Sets and Possibility Theory: Recent Development Ed. YagerR R (Pergamon Press, New York) pp xi–xii
40.
ZadehL A, 1983, “The role of fuzzy logic in the management of uncertainty in expert systems”Fuzzy Sets and Systems11199–227
41.
ZadehL A, 1985, “Foreword”, in Approximate Reasoning in Expert Systems Eds GuptaM MKandelABandlerWKiszkaJ B (North-Holland, Amsterdam) pp vii–viii
42.
ZadehL AFuK STanakaKShimuraM, 1975Fuzzy Sets and Their Applications to Cognitive and Decision Processes (Academic Press, New York)
43.
ZebdaA, 1984, “The investigation of cost variances: A fuzzy set theory approach”Decision Sciences15359–388
44.
ZnotinasN MHipelK W, 1979, “Comparison of alternative engineering designs”Water Resources Bulletin1544–59