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Optimization-based Cosmetic Formulation: Integration of Mechanistic Model, Surrogate Model, and Heuristics
  • Xiang Zhang,
  • Teng Zhou,
  • Ka Ng
Xiang Zhang
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Teng Zhou
Max Planck Institute for Dynamics of Complex Technical Systems
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Ka Ng
Hong Kong University of Science and Technology
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Peer review status:UNDER REVIEW

13 May 2020Submitted to AIChE Journal
14 May 2020Submission Checks Completed
14 May 2020Assigned to Editor
26 May 2020Reviewer(s) Assigned
08 Jul 2020Editorial Decision: Revise Major
22 Jul 20201st Revision Received
22 Jul 2020Submission Checks Completed
22 Jul 2020Assigned to Editor
23 Jul 2020Reviewer(s) Assigned

Abstract

Multiple functional and hard-to-quantify sensorial product attributes that can be satisfied by a large number of cosmetic ingredients are required in the design of cosmetics. To overcome this challenge, a new optimization-based approach for expediting cosmetic formulation is presented. It exploits the use of a hierarchy of models in an iterative manner to refine the search for creating the highest-quality cosmetic product. First, a systematic procedure is proposed for optimization problem formulation, where the cosmetic formulation problem is defined, design variables are specified, and a set of models for sensorial perception and desired product properties are identified. Then, a solution strategy that involves iterative model adoption and two numerical techniques (i.e., generalized disjunctive programming reformulation and model substitution) is applied to improve the efficiency of solving the optimization problem and to find better solutions. The applicability of the proposed procedure and solution strategy is illustrated with a perfume formulation example.