Comparison of different MINLP methods applied on certain chemical engineering problems

Hans Skrifvars; Iiro Harjunkoski; Tapio Westerlund; Zdravko Kravanja; Ray Pörn

Comparison of different MINLP methods applied on certain chemical engineering problems

Hans Skrifvars^*, Iiro Harjunkoski, Tapio Westerlund, Zdravko Kravanja, Ray Pörn

^*Corresponding author for this work

Not published at Aalto University

Research output: Contribution to journal › Review Article › peer-review

8 Citations (Scopus)

Abstract

In this paper a comparison of some of the methods available for solving mixed integer non-linear programming (MINLP) problems is presented. Since some methods solve both a mixed integer linear programming (MILP) master problem and non-linear programming (NLP) subproblems during the iterations, while others only solve MILP master problems, a comparison of the computer resources needed for the optimization is presented. The methods are applied on a number of significant chemical engineering problems involving both MINLP problems (with a variety in the degree of discreteness and complexity) and some strict integer non-linear programming (INLP) problems. From the results, it is to be seen that a comparison of only the number of iterations needed in the optimization, doesn't allways measure the actual required resources of the optimization.

Original language	English
Journal	Computers and Chemical Engineering
Volume	20
Issue number	SUPPL.1
Publication status	Published - 1996
MoE publication type	A2 Review article in a scientific journal

Keywords

Design Optimization
INLP
Mathematical Programming
MILP
MINLP
Optimization
Process Integration
Process Synthesis

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title = "Comparison of different MINLP methods applied on certain chemical engineering problems",

abstract = "In this paper a comparison of some of the methods available for solving mixed integer non-linear programming (MINLP) problems is presented. Since some methods solve both a mixed integer linear programming (MILP) master problem and non-linear programming (NLP) subproblems during the iterations, while others only solve MILP master problems, a comparison of the computer resources needed for the optimization is presented. The methods are applied on a number of significant chemical engineering problems involving both MINLP problems (with a variety in the degree of discreteness and complexity) and some strict integer non-linear programming (INLP) problems. From the results, it is to be seen that a comparison of only the number of iterations needed in the optimization, doesn't allways measure the actual required resources of the optimization.",

keywords = "Design Optimization, INLP, Mathematical Programming, MILP, MINLP, Optimization, Process Integration, Process Synthesis",

author = "Hans Skrifvars and Iiro Harjunkoski and Tapio Westerlund and Zdravko Kravanja and Ray P{\"o}rn",

year = "1996",

language = "English",

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journal = "Computers and Chemical Engineering ",

issn = "0098-1354",

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T1 - Comparison of different MINLP methods applied on certain chemical engineering problems

AU - Skrifvars, Hans

AU - Harjunkoski, Iiro

AU - Westerlund, Tapio

AU - Kravanja, Zdravko

AU - Pörn, Ray

PY - 1996

Y1 - 1996

N2 - In this paper a comparison of some of the methods available for solving mixed integer non-linear programming (MINLP) problems is presented. Since some methods solve both a mixed integer linear programming (MILP) master problem and non-linear programming (NLP) subproblems during the iterations, while others only solve MILP master problems, a comparison of the computer resources needed for the optimization is presented. The methods are applied on a number of significant chemical engineering problems involving both MINLP problems (with a variety in the degree of discreteness and complexity) and some strict integer non-linear programming (INLP) problems. From the results, it is to be seen that a comparison of only the number of iterations needed in the optimization, doesn't allways measure the actual required resources of the optimization.

AB - In this paper a comparison of some of the methods available for solving mixed integer non-linear programming (MINLP) problems is presented. Since some methods solve both a mixed integer linear programming (MILP) master problem and non-linear programming (NLP) subproblems during the iterations, while others only solve MILP master problems, a comparison of the computer resources needed for the optimization is presented. The methods are applied on a number of significant chemical engineering problems involving both MINLP problems (with a variety in the degree of discreteness and complexity) and some strict integer non-linear programming (INLP) problems. From the results, it is to be seen that a comparison of only the number of iterations needed in the optimization, doesn't allways measure the actual required resources of the optimization.

KW - Design Optimization

KW - INLP

KW - Mathematical Programming

KW - MILP

KW - MINLP

KW - Optimization

KW - Process Integration

KW - Process Synthesis

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M3 - Review Article

AN - SCOPUS:0029715057

VL - 20

JO - Computers and Chemical Engineering

JF - Computers and Chemical Engineering

SN - 0098-1354

IS - SUPPL.1

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