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- W2840821799 abstract "In any design activity, the basic problem is to find the best obtainable solution to a collection of constraints and criteria. Designers seek to find a set of values for the design variables that satisfies ALL the constraints and optimizes ALL the criteria. This task, which is usually made difficult by the multitude of constraints involved, can be rendered impossible if some of the constraints and criteria conflict.When constraints conflict there is no solution to the design problem. It is not unusual then for designers to 'relax' one or more of the constraints (i.e., violate them to some small degree) in order to identify some acceptable (satisfactory) solution. Rather than view constraints as having crisp boundaries, designers tend to consider the boundaries as fuzzy, and constraints as being satisfied to varying degrees. None of the conventional approaches to satisfying constraint systems actually take into account this characteristic fuzziness.In this work, we propose a technique that incorporates fuzziness. We specify constraints as fuzzy relations with associated membership functions that express how well a designer (or client) believes the constraints are satisfied. We also specify criteria as fuzzy goals with membership functions. We define a design problem as a set of constraints and criteria with their associated membership functions. For a given design alternative (i.e., a given set of values for the design variables), each membership function measures how well (i.e., as a membership grade) the set of values satisfies the corresponding constraint or criteria. We obtain an overall membership (satisfaction) grade for the alternative by aggregating the grades for ALL constraints and criteria using an appropriate aggregation operator.In the first part of the research, we propose appropriate membership functions for mathematical design constraints and criteria, by considering their properties specific to design. This representation enables a designer to capture constraints and criteria at any level of specificity. In the second part, which represents a decision model, we propose appropriate aggregation operators for combining membership grades. The two parts, taken together, provide a means for designers to explore design alternatives by relaxing constraints and then investigating the effect of the relaxation on alternatives under different tradeoff strategies." @default.
- W2840821799 created "2018-07-19" @default.
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- W2840821799 date "1998-03-17" @default.
- W2840821799 modified "2023-09-26" @default.
- W2840821799 title "Constraint relaxation: a technique for exploring design alternatives" @default.
- W2840821799 hasPublicationYear "1998" @default.
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