Solving Multi-objective MILP Problems in Process Synthesis using the Multi-Criteria Branch and Bound Algorithm

The paper briefly describes the problem of process synthesis in the area of chemical engineering, and suggests its formulation as a Multi‐Objective Programming problem. Process synthesis optimization is usually modeled as Mixed Integer Linear Programming (MILP) or Mixed Integer Non‐Linear Programmin...

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Vydáno v:Chemical engineering & technology Ročník 28; číslo 12; s. 1500 - 1510
Hlavní autoři: Mavrotas, G., Diakoulaki, D.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Weinheim WILEY-VCH Verlag 01.12.2005
WILEY‐VCH Verlag
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ISSN:0930-7516, 1521-4125
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Abstract The paper briefly describes the problem of process synthesis in the area of chemical engineering, and suggests its formulation as a Multi‐Objective Programming problem. Process synthesis optimization is usually modeled as Mixed Integer Linear Programming (MILP) or Mixed Integer Non‐Linear Programming (MINLP) with an economic objective function. We claim that incorporating more criteria (e.g., environmental criteria) in this kind of combinatorial optimization problem offers the decision makers the opportunity to refine their final decision by examining more than one solution (a set of efficient or Pareto optimal solutions instead of one optimal solution). For solving the multi‐objective process synthesis problem, an improved version of the Multi‐Criteria Branch and Bound (MCBB) algorithm, which has been developed by the same authors, is used. MCBB is a vector maximization algorithm capable of deriving all efficient points (supported and unsupported), for small and medium sized Multi‐Objective MILP problems. The application of MCBB in two examples from process synthesis is also presented. The formulation of process synthesis in chemical engineering as a Multi‐Objective Programming is discussed. An improved version of the Multi‐Criteria Branch and Bound (MCBB) algorithm is used, which is a vector maximization algorithm capable of deriving all efficient points (supported and unsupported) for small and medium sized Multi‐Objective MILP problems. The application of MCBB in two examples from process synthesis is presented.
AbstractList The paper briefly describes the problem of process synthesis in the area of chemical engineering, and suggests its formulation as a Multi‐Objective Programming problem. Process synthesis optimization is usually modeled as Mixed Integer Linear Programming (MILP) or Mixed Integer Non‐Linear Programming (MINLP) with an economic objective function. We claim that incorporating more criteria (e.g., environmental criteria) in this kind of combinatorial optimization problem offers the decision makers the opportunity to refine their final decision by examining more than one solution (a set of efficient or Pareto optimal solutions instead of one optimal solution). For solving the multi‐objective process synthesis problem, an improved version of the Multi‐Criteria Branch and Bound (MCBB) algorithm, which has been developed by the same authors, is used. MCBB is a vector maximization algorithm capable of deriving all efficient points (supported and unsupported), for small and medium sized Multi‐Objective MILP problems. The application of MCBB in two examples from process synthesis is also presented. The formulation of process synthesis in chemical engineering as a Multi‐Objective Programming is discussed. An improved version of the Multi‐Criteria Branch and Bound (MCBB) algorithm is used, which is a vector maximization algorithm capable of deriving all efficient points (supported and unsupported) for small and medium sized Multi‐Objective MILP problems. The application of MCBB in two examples from process synthesis is presented.
Author Mavrotas, G.
Diakoulaki, D.
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Issue 12
Keywords Chemical engineering
Branch and bound method
Linear programming
Mixed integer programming
Non linear programming
Objective function
Combinatorial optimization
Algorithm
Modeling
Mathematical programming
Language English
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Snippet The paper briefly describes the problem of process synthesis in the area of chemical engineering, and suggests its formulation as a Multi‐Objective Programming...
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SubjectTerms Applications of mathematics to chemical engineering. Modeling. Simulation. Optimization
Applied sciences
Chemical engineering
Exact sciences and technology
Optimization
Process engineering
Process optimization
Title Solving Multi-objective MILP Problems in Process Synthesis using the Multi-Criteria Branch and Bound Algorithm
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Volume 28
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