- author = "Tomasz P. Pawlak and Krzysztof Krawiec",
- title = "Synthesis of Constraints for Mathematical Programming with One-Class Genetic Programming",
- journal = "IEEE Transactions on Evolutionary Computation",
- year = "2019",
- volume = "23",
- number = "1",
- pages = "117--219",
- month = feb,
- keywords = "genetic algorithms, genetic programming, linear programming, constraint acquisition, business process, model induction, wine quality",
- ISSN = "1089-778X",
-
URL = "
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8357939",
-
DOI = "
10.1109/TEVC.2018.2835565",
- size = "12 page",
- abstract = "Mathematical Programming (MP) models are common in optimization of real-world processes. Models are usually built by optimization experts in an iterative manner: an imperfect model is continuously improved until it approximates the reality well-enough and meets all technical requirements (e.g., linearity). To facilitate this task, we propose a Genetic One-Class Constraint Synthesis method (GOCCS). Given a set of exemplary states of normal operation of a business process, GOCCS synthesizes constraints in Linear Programming or Non-linear Programming form. The synthesized constraints can be then paired with an arbitrary objective function and supplied to an off-the-shelf solver to find optimal parameters of the process. We assess GOCCS on three families of MP benchmarks and conclude promising results. We also apply it to a real-world process of wine production and optimize that process.",
-
notes = "'The best QP model synthesized for white wine
is:'
also known as \cite{8357939}",
