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In this paper, we consider both the modelling and optimization of preferences in problems of constraint-based temporal reasoning.
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We then generalize the powerful search strategies from decision-based DTP literature to accomplish the efficient optimization of temporal preferences.
In contrast to the previous state-of-the-art system (which addresses the optimization of temporal preferences using a SAT formulation), we instead employ a meta-CSP search space that has traditionally been used to solve DTPs without preferences.
The proposed self adaptive modification method makes use of three sub-modifications to give each bat (solution) a choice of preferences during the optimization process.
To incorporate preferences into multi-objective optimization algorithms, the modeling and articulation of preferences must be considered.
The framework of set-based evolutionary optimization integrating preferences is illustrated in "PSEA-m".
Optimization methods with a priori and a posteriori articulation of preferences are used to solve the problem.
In addition, we evaluated two scenarios to analyze a different number of preferences and their impact on the optimization process.
Optimization of the aromatic region showed preference for 5,8-disubstitution pattern in both the scaffolds examined while favoring the n-propyl moiety for the C-1 position.
Future studies are needed, to explore whether personalization of format and the level of detail of content (particularly relating to numerical data) of P-DAs to users' preferences may enable optimization of knowledge translation outcomes, or at least be non-inferior to current methods, but potentially preferred by some users.
The potential of the larvivorous fish Gambusia (Gambusia affinis and G. holbrooki; Pyke 2005) to ingest large numbers of mosquito larvae led to a series of laboratory-based studies on mosquito larval prey preferences and the optimization of systems to propagate these fish.
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