NBI

Normal-boundary intersection: A new method for generating the Pareto surface in nonlinear multicriteria optimization problems This paper proposes an alternate method for finding several Pareto optimal points for a general nonlinear multicriteria optimization problem. Such points collectively capture the trade-off among the various conflicting objectives. It is proved that this method is independent of the relative scales of the functions and is successful in producing an evenly distributed set of points in the Pareto set given an evenly distributed set of parameters, a property which the popular method of minimizing weighted combinations of objective functions lacks. Further, this method can handle more than two objectives while retaining the computational efficiency of continuation-type algorithms. This is an improvement over continuation techniques for tracing the trade-off curve since continuation strategies cannot easily be extended to handle more than two objectives. (Source: http://plato.asu.edu)


References in zbMATH (referenced in 141 articles , 1 standard article )

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  1. Bento, G. C.; Cruz Neto, J. X.; López, G.; Soubeyran, Antoine; Souza, J. C. O.: The proximal point method for locally Lipschitz functions in multiobjective optimization with application to the compromise problem (2018)
  2. Denysiuk, Roman; Silva, Cristiana J.; Torres, Delfim F. M.: Multiobjective optimization to a TB-HIV/AIDS coinfection optimal control problem (2018)
  3. Hosseininasab, Seyyed-Mohammadreza; Shetab-Boushehri, Seyyed-Nader; Hejazi, Seyed Reza; Karimi, Hadi: A multi-objective integrated model for selecting, scheduling, and budgeting road construction projects (2018)
  4. Kirlik, Gokhan; Sayın, Serpil: Bilevel programming for generating discrete representations in multiobjective optimization (2018)
  5. Banasik, Aleksander; Kanellopoulos, Argyris; Claassen, G. D. H.; Bloemhof-Ruwaard, Jacqueline M.; van der Vorst, Jack G. A. J.: Assessing alternative production options for eco-efficient food supply chains using multi-objective optimization (2017)
  6. Burachik, R. S.; Kaya, C. Y.; Rizvi, M. M.: A new scalarization technique and new algorithms to generate Pareto fronts (2017)
  7. Cao, Yongtao; Smucker, Byran J.; Robinson, Timothy J.: A hybrid elitist Pareto-based coordinate exchange algorithm for constructing multi-criteria optimal experimental designs (2017)
  8. Lin, Kuan-Min; Ehrgott, Matthias; Raith, Andrea: Integrating column generation in a method to compute a discrete representation of the non-dominated set of multi-objective linear programmes (2017)
  9. Liu, Chongyang; Gong, Zhaohua; Teo, Kok Lay; Sun, Jie; Caccetta, Louis: Robust multi-objective optimal switching control arising in 1,3-propanediol microbial fed-batch process (2017)
  10. Liu, Xin; Reynolds, Albert C.: Robust gradient-based multiobjective optimization for the generation of well controls to maximize the net-present-value of production under geological uncertainty (2017)
  11. Martin, Benjamin; Goldsztejn, Alexandre; Granvilliers, Laurent; Jermann, Christophe: Constraint propagation using dominance in interval branch & bound for nonlinear biobjective optimization (2017)
  12. Sánchez, Helem Sabina; Visioli, Antonio; Vilanova, Ramon: Optimal Nash tuning rules for robust PID controllers (2017)
  13. Wang, Honggang: Multi-objective retrospective optimization using stochastic zigzag search (2017)
  14. Cheng, Junheng; Chu, Feng; Chu, Chengbin; Xia, Weili: Bi-objective optimization of single-machine batch scheduling under time-of-use electricity prices (2016)
  15. Fliege, Jörg; Vaz, A. Ismael F.: A method for constrained multiobjective optimization based on SQP techniques (2016)
  16. Jornada, Daniel; Leon, V. Jorge: Biobjective robust optimization over the efficient set for Pareto set reduction (2016)
  17. Liu, Xin; Reynolds, Albert C.: Gradient-based multi-objective optimization with applications to waterflooding optimization (2016)
  18. Liu, Xin; Reynolds, Albert C.: A multiobjective steepest descent method with applications to optimal well control (2016)
  19. Martin, Benjamin; Goldsztejn, Alexandre; Granvilliers, Laurent; Jermann, Christophe: On continuation methods for non-linear bi-objective optimization: towards a certified interval-based approach (2016)
  20. Nowé, Ann; Brys, Tim: A gentle introduction to reinforcement learning (2016)

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