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An algorithm for multiparametric mixed integer semidefinite optimization
42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475), 2004Recently a new and efficient algorithm for mixed integer semidefinite programming (MISDP) was introduced. The algorithm is applicable to robust control of a general class of hybrid systems but despite its benefits in this regard, it may prove too computationally expensive for online optimisation in a range of applications.
Camile Rowe, Jan M. Maciejowski
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Minotaur: a mixed-integer nonlinear optimization toolkit
Mathematical Programming Computation, 2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ashutosh Mahajan +4 more
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Split cuts for robust mixed-integer optimization
Operations Research Letters, 2012zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Haus, U., Pfeuffer, F.
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Fuzzy programming for mixed-integer optimization problems
Artificial Life and Robotics, 2011Mixed-integer optimization problems belong to the group of NP-hard combinatorial problems. Therefore, they are difficult to search for global optimal solutions. Mixed-integer optimization problems are always described by precise mathematical programming models.
Yung-Chin Lin +4 more
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An optimality cut for mixed integer linear programs
European Journal of Operational Research, 1999zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gilbert Laporte, Frédéric Semet
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Multitarget Tracking via Mixed Integer Optimization
IEEE Transactions on Automatic Control, 2018Given a set of target detections over several time periods, this paper addresses the multitarget tracking (MTT) problem of optimally assigning detections to targets and estimating the trajectory of the targets over time. MTT has been studied in the literature via predominantly probabilistic methods.
Dimitris Bertsimas +2 more
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Mixed-Integer Linear Optimization
2017In this chapter, we study mixed-integer linear optimization problems, which are also known as mixed-integer linear programming problems (MILPPs). MILPPs are problems with an objective function and constraints that all linear in the decision variables.
Ramteen Sioshansi, Antonio J. Conejo
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Nonlinear and Mixed-Integer Optimization
1995Filling a void in chemical engineering and optimization literature, this book presents the theory and methods for nonlinear and mixed-integer optimization, and their applications in the important area of process synthesis. Other topics include modeling issues in process synthesis, and optimization-based approaches in the synthesis of heat recovery ...
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2011
In this chapter we extend the problem class of continuous optimal control problems discussed in chapter 1 to include control functions that may at each point in time attain only a finite number of values from a discrete set. We briefly survey different approaches for the solution of the discretized Mixed–Integer Optimal Control Problem (MIOCP), such as
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In this chapter we extend the problem class of continuous optimal control problems discussed in chapter 1 to include control functions that may at each point in time attain only a finite number of values from a discrete set. We briefly survey different approaches for the solution of the discretized Mixed–Integer Optimal Control Problem (MIOCP), such as
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Mixed-Integer Linear Optimization
1995This chapter provides an introduction to the basic notions in Mixed-Integer Linear Optimization. Sections 5.1 and 5.2 present the motivation, formulation, and outline of methods. Section 5.3 discusses the key ideas in a branch and bound framework for mixed-integer linear programming problems.
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