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Optimization mixed integer nonlinear program

One of the approaches that can be used in design is to carry out structural and parameter optimization of a superstructure. The structural optimization required can be carried out using mixed integer linear programming in the case of a linear problem or mixed integer nonlinear programming in the case of a nonlinear problem. Stochastic optimization can also be very effective for structural optimization problems. [Pg.54]

Kalitventzeff, B. Mixed Integer Nonlinear Programming and its Application to the Management of Utility Networks. Eng Optim 18 183-207 (1991). [Pg.440]

Bauer, M. H. and J. Stichlmair. Design and Economic Optimization of Azeotropic Distillation Process Using Mixed-Integer Nonlinear Programming. Comput Chem Eng 22 1271-1286 (1998). [Pg.458]

Flowsheet optimization is also regarded as a key task in the structural optimization of a flowsheet. As a described in the introduction, structural optimization for process design can be formulated as a mixed integer nonlinear program (MINLP). This then allows for addition or replacement of existing units, and consideration of a number of design options simultaneously. In these formulations individual units are turned on and off over the course of the optimization, as suggested by the MINLP master problem. [Pg.213]

A wide range of nonlinear optimization problems involve integer or discrete variables in addition to the continuous variables. These classes of optimization problems arise from a variety of applications and are denoted as Mixed-Integer Nonlinear Programming MINLP problems. [Pg.109]

The general mathematical model of the superstructure presented in step 2 of the outline, and indicated as (7.1), has a mixed set of 0 - 1 and continuous variables and as a result is a mixed-integer optimization model. If any of the objective function and constraints is nonlinear, then (7.1) is classified as mixed- integer nonlinear programming MINLP problem. [Pg.235]

McKinney, D. C., and Lin, M. D. (1995). "Approximate mixed-integer nonlinear programming methods for optimal aquifer remediation design." Water Resour. Res., 31(3), 731-740. [Pg.20]

A process-synthesis problem can be formulated as a combination of tasks whose goal is the optimization of an economic objective function subject to constraints. Two types of mathematical techniques are the most used mixed-integer linear programming (MILP), and mixed-integer nonlinear programming (MINLP). [Pg.17]

Kocis, G. R., A Mixed-Integer Nonlinear Programming Approach to Structural Flowsheet Optimization. Ph.D. thesis, Carnegie Mellon University, Pittsburgh, 1988. [Pg.523]

Mixed integer nonlinear programming Multi-criteria optimization... [Pg.241]

M. Tawarmalani, V. Sahinidis, Global Optimization in Continuous and Mixed-Integer Nonlinear Programming Theory, Algorithms, Software, and Applications, Kluwer, Boston, 2001. [Pg.34]

Kocis, G. R., and Grossmann, I. E. Global Optimization of Nonconvex Mixed-Integer Nonlinear Programming (MINLP) Problems in Process Synthesis, Ind. Eng. Chem. Res. 27,1407 (1988). [Pg.243]

One approach to making discrete design decisions is to pose a mixed-integer nonlinear program (MINLP) and apply a suitable optimization method to the selection of discrete design parameters. We have not adopted this approach for the following reasons. [Pg.343]


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Integer

Mixed nonlinear

Mixed optimization

Mixed-integer nonlinear optimization

Mixed-integer nonlinear programming optimization

Mixed-integer nonlinear programming optimization

Optimization mixed integer programming

Optimization nonlinear

Optimization nonlinear program

Program optimization

Programmed optimization

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