ϵ-OA for the solution of bi-objective generalized disjunctive programming problems in the synthesis of nonlinear process networks

•A novel algorithm (ϵ-OA) for generating efficient solutions for bi-objective GDPs is presented.•Theoretical characterization of the ϵ-OA is provided.•The ϵ-OA is illustrated on two well-known benchmark problems.•Comparative analysis of the performance illustrates the superiority of the novel ϵ-OA a...

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Vydáno v:Computers & chemical engineering Ročník 72; s. 199 - 209
Hlavní autoři: Fattahi, Ali, Turkay, Metin
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 02.01.2015
Témata:
Generalized disjunctive programming
Mixed-integer nonlinear programming
Multiple criteria optimization
Outer approximation
ϵ-Constraint method
ϵ-Constraint method
Generalized disjunctive programming
Outer approximation
Mixed-integer nonlinear programming
Multiple criteria optimization
ISSN:0098-1354, 1873-4375
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Shrnutí:•A novel algorithm (ϵ-OA) for generating efficient solutions for bi-objective GDPs is presented.•Theoretical characterization of the ϵ-OA is provided.•The ϵ-OA is illustrated on two well-known benchmark problems.•Comparative analysis of the performance illustrates the superiority of the novel ϵ-OA algorithm over straightforward implementations. There has been an increasing interest in multicriteria optimization (MCO) of nonlinear process network problems in recent years. Several mathematical models have been developed and solved using MCO methodologies including ϵ-constraint, weighted sum, and minimum distance. In this paper, we investigate the bi-objective nonlinear network synthesis problem and propose an effective algorithm, ϵ-OA, based on augmented ϵ-constraint and logic-based outer approximation (OA). We provide theoretical characterization of the proposed algorithm and show that the solutions generated are efficient. We illustrate the effectiveness of our novel algorithm on two benchmark problems. The ϵ-OA is compared to the straightforward use of OA with augmented ϵ-constraint algorithm (ϵ-con+OA), the augmented ϵ-constraint without OA (ϵ-MINLP), and the traditional ϵ-constraint (T-ϵ-con). Based on the results, our novel algorithm is very effective in solving the bi-objective generalized disjunctive programming problems in the synthesis of process networks.
ISSN:0098-1354
1873-4375
DOI:10.1016/j.compchemeng.2014.04.004