Logical Fuzzy Optimization
This work addresses fuzzy optimization problems in domains like resource allocation, but it appears incremental as it builds on existing fuzzy answer set optimization programming.
The authors introduced a logical framework for representing and reasoning about fuzzy optimization problems using fuzzy answer set optimization programming, and demonstrated its application to a fuzzy water allocation optimization problem.
We present a logical framework to represent and reason about fuzzy optimization problems based on fuzzy answer set optimization programming. This is accomplished by allowing fuzzy optimization aggregates, e.g., minimum and maximum in the language of fuzzy answer set optimization programming to allow minimization or maximization of some desired criteria under fuzzy environments. We show the application of the proposed logical fuzzy optimization framework under the fuzzy answer set optimization programming to the fuzzy water allocation optimization problem.