{'fraction_non_alphanumeric': 0.023809523809523808, 'fraction_numerical': 0.010651629072681704, 'mean_word_length': 5.095419847328245, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A fuzzy decision model for conceptual design

In conceptual design, there are decision problems wherein the information cannot be assessed precisely in a quantitative manner, but may be assessed in a qualitative manner. This necessitates a linguistic descript on a decision problem in conceptual design. Based on this viewpoint a new fuzzy decision model for selecting the preferred conceptual design from a set of alternatives is presented. The model uses a structured form of linguistic information called “General-Opinion and Desire,” or GD. The first part of GD is a set of propositions that encode the general opinion about a conceptual design alternative for a criterion using a set of quantifiers. The other part of GD is a special proposition that encodes the desire, or requirement, for a preferred conceptual design alternative. If appropriate truth-values, taken from the interval [0, 1], are assigned to these propositions, one can determine how clearly the conceptual design alternative under consideration is known (certainty compliance) and how desirable the alternative is (desire compliance). Two functions are developed to measure the certainty and desire compliances. An aggregation function is also developed to aggregate the payoffs of certainty and desire compliances, in case the selection is made by using a set of criteria. Using the case of a real-life conceptual design problem, it is shown that the proposed decision model is useful in selecting the preferred conceptual design from a given set of alternatives. © 2005 Wiley Periodicals, Inc. Syst Eng 8: 296–308, 2005