Automated reformulation of disjunctive constraints in MINLP optimization

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    In this paper, a general method for handling disjunctive constraints in a MINLP optimization problem is presented. This method automates the reformulation of an, in a abstract modeling language given, optimization problem into a mathematical problem that is solvable with existing optimization tools. This implementation can use common MILP solvers for linear problems and nonlinear methods for quasi-convex optimization problems. It also includes the possibility to use the logics in the system and solve the system logically using subproblems.
    Original languageUndefined/Unknown
    Pages (from-to)S11–S14
    Number of pages4
    JournalComputers and Chemical Engineering
    Publication statusPublished - 1999
    MoE publication typeA1 Journal article-refereed


    • disjunctive constraints
    • mixed integer non-linear programming
    • process synthesis
    • scheduling problems
    • transformations

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