Pop-the parametric optimization toolbox
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Copyright American Institute of Chemical Engineers. All rights reserved. Recent years have seen an increased interest in multi-parametric programming (mp-P), in large part due to the ever increasing number of areas where mp-P can be applied such as bilevel programming, reactive scheduling and decentralized control. This in turn has led to significant theoretical advances in fields such as multi-parametric mixedinteger programming, multi-parametric moving horizon estimation and global mp-P [1]. For the solution of the underlying mp-P problems, currently only one solver package is openly available, namely the MPT toolbox [2]. Albeit being very complete and providing a wide array of capabilities, the MPT toolbox is computationally limiting when larger problems are considered. Additionally, as it has its own class and object definitions, software interoperability becomes a challenging process especially during the closed-loop validation of the derived controllers.