Baehyun Min | Seoul National University (original) (raw)

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Papers by Baehyun Min

Research paper thumbnail of Pareto-based multi-objective history matching with respect to individual production performance in a heterogeneous reservoir

Journal of Petroleum Science and Engineering, 2014

pareto-based history matching trade-off evolutionary algorithm preference-ordering objective-redu... more pareto-based history matching trade-off evolutionary algorithm preference-ordering objective-reduction a b s t r a c t

Research paper thumbnail of Development of Pareto-based evolutionary model integrated with dynamic goal programming and successive linear objective reduction

Applied Soft Computing, 2015

This study investigates the coupling effects of objective-reduction and preference-ordering schem... more This study investigates the coupling effects of objective-reduction and preference-ordering schemes on the search efficiency in the evolutionary process of multi-objective optimization. The difficulty in solving a many-objective problem increases with the number of conflicting objectives. Degenerated objective space can enhance the multi-directional search toward the multi-dimensional Pareto-optimal front by eliminating redundant objectives, but it is difficult to capture the true Pareto-relation among objectives in the non-optimal solution domain. Successive linear objective-reduction for the dimensionality-reduction and dynamic goal programming for preference-ordering are developed individually and combined with a multi-objective genetic algorithm in order to reflect the aspiration levels for the essential objectives adaptively during optimization. The performance of the proposed framework is demonstrated in redundant and non-redundant benchmark test problems. The preference-ordering approach induces the non-dominated solutions near the front despite enduring a small loss in diversity of the solutions. The induced solutions facilitate a degeneration of the Pareto-optimal front using successive linear objectivereduction, which updates the set of essential objectives by excluding non-conflicting objectives from the set of total objectives based on a principal component analysis. Salient issues related to real-world problems are discussed based on the results of an oil-field application. (C. Park). been proposed to represent the POF by achieving two orthogonal goals simultaneously: convergence of solutions as close to the POF as possible and diversity of solutions as uniformly distributed along the POF as possible .

Research paper thumbnail of Production-System Optimization of Gas Fields Using Hybrid Fuzzy/Genetic Approach

SPE Journal, 2010

... In the petroleum industry, fuzzy logic has been put to work in many different areas since the... more ... In the petroleum industry, fuzzy logic has been put to work in many different areas since the early 1990s, including reservoir characterization (Hambalek and Gonzalez 2003; Lim and Kim 2004; Rafiei et al. 2009; Shokir 2006; Soto et al. ... (2009); Shokir (2006); Soto et al. ...

Research paper thumbnail of Pareto-based multi-objective history matching with respect to individual production performance in a heterogeneous reservoir

Journal of Petroleum Science and Engineering, 2014

pareto-based history matching trade-off evolutionary algorithm preference-ordering objective-redu... more pareto-based history matching trade-off evolutionary algorithm preference-ordering objective-reduction a b s t r a c t

Research paper thumbnail of Development of Pareto-based evolutionary model integrated with dynamic goal programming and successive linear objective reduction

Applied Soft Computing, 2015

This study investigates the coupling effects of objective-reduction and preference-ordering schem... more This study investigates the coupling effects of objective-reduction and preference-ordering schemes on the search efficiency in the evolutionary process of multi-objective optimization. The difficulty in solving a many-objective problem increases with the number of conflicting objectives. Degenerated objective space can enhance the multi-directional search toward the multi-dimensional Pareto-optimal front by eliminating redundant objectives, but it is difficult to capture the true Pareto-relation among objectives in the non-optimal solution domain. Successive linear objective-reduction for the dimensionality-reduction and dynamic goal programming for preference-ordering are developed individually and combined with a multi-objective genetic algorithm in order to reflect the aspiration levels for the essential objectives adaptively during optimization. The performance of the proposed framework is demonstrated in redundant and non-redundant benchmark test problems. The preference-ordering approach induces the non-dominated solutions near the front despite enduring a small loss in diversity of the solutions. The induced solutions facilitate a degeneration of the Pareto-optimal front using successive linear objectivereduction, which updates the set of essential objectives by excluding non-conflicting objectives from the set of total objectives based on a principal component analysis. Salient issues related to real-world problems are discussed based on the results of an oil-field application. (C. Park). been proposed to represent the POF by achieving two orthogonal goals simultaneously: convergence of solutions as close to the POF as possible and diversity of solutions as uniformly distributed along the POF as possible .

Research paper thumbnail of Production-System Optimization of Gas Fields Using Hybrid Fuzzy/Genetic Approach

SPE Journal, 2010

... In the petroleum industry, fuzzy logic has been put to work in many different areas since the... more ... In the petroleum industry, fuzzy logic has been put to work in many different areas since the early 1990s, including reservoir characterization (Hambalek and Gonzalez 2003; Lim and Kim 2004; Rafiei et al. 2009; Shokir 2006; Soto et al. ... (2009); Shokir (2006); Soto et al. ...

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