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 217 articles , 1 standard article )

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  1. Borgonjon, Tessa; Maenhout, Broos: A two-phase Pareto front method for solving the bi-objective personnel task rescheduling problem (2022)
  2. Chagas, Jonatas B. C.; Wagner, Markus: A weighted-sum method for solving the bi-objective traveling thief problem (2022)
  3. Gonçalves, M. L. N.; Lima, F. S.; Prudente, L. F.: A study of Liu-Storey conjugate gradient methods for vector optimization (2022)
  4. Hamada, Naoki; Ichiki, Shunsuke: Free disposal hull condition to verify when efficiency coincides with weak efficiency (2022)
  5. Reiners, Malena; Klamroth, Kathrin; Heldmann, Fabian; Stiglmayr, Michael: Efficient and sparse neural networks by pruning weights in a multiobjective learning approach (2022)
  6. Sahinkoc, H. Mert; Bilge, Ümit: A reference set based many-objective co-evolutionary algorithm with an application to the knapsack problem (2022)
  7. Ulusoy, Aly-Joy; Pecci, Filippo; Stoianov, Ivan: Bi-objective design-for-control of water distribution networks with global bounds (2022)
  8. Aliano Filho, Angelo; Moretti, Antonio Carlos; Pato, Margarida Vaz; de Oliveira, Washington Alves: An exact scalarization method with multiple reference points for bi-objective integer linear optimization problems (2021)
  9. Assunção, P. B.; Ferreira, O. P.; Prudente, L. F.: Conditional gradient method for multiobjective optimization (2021)
  10. Audet, Charles; Bigeon, Jean; Cartier, Dominique; Le Digabel, Sébastien; Salomon, Ludovic: Performance indicators in multiobjective optimization (2021)
  11. Bolten, Matthias; Doganay, Onur Tanil; Gottschalk, Hanno; Klamroth, Kathrin: Tracing locally Pareto-optimal points by numerical integration (2021)
  12. Ghaznavi, M.; Akbari, F.; Khorram, E.: Optimality conditions via a unified direction approach for (approximate) efficiency in multiobjective optimization (2021)
  13. Gkaragkounis, K. T.; Papoutsis-Kiachagias, E. M.; Giannakoglou, K. C.: Adjoint-assisted Pareto front tracing in aerodynamic and conjugate heat transfer shape optimization (2021)
  14. Hollermann, Dinah Elena; Goerigk, Marc; Hoffrogge, Dörthe Franzisca; Hennen, Maike; Bardow, André: Flexible here-and-now decisions for two-stage multi-objective optimization: method and application to energy system design selection (2021)
  15. Lovison, Alberto; Miettinen, Kaisa: On the extension of the \textscdirectalgorithm to multiple objectives (2021)
  16. Sun, Jinghe; Zhang, Guohui; Lu, Jiao; Zhang, Wenqiang: A hybrid many-objective evolutionary algorithm for flexible job-shop scheduling problem with transportation and setup times (2021)
  17. Tsionas, Mike G.: Multi-criteria optimization in regression (2021)
  18. Yuan, Jiawei: A constraint handling technique using compound distance for solving constrained multi-objective optimization problems (2021)
  19. Zhang, Kai; Shen, Chaonan; He, Juanjuan; Yen, Gary G.: Knee based multimodal multi-objective evolutionary algorithm for decision making (2021)
  20. Zouache, Djaafar; Ben Abdelaziz, Fouad; Lefkir, Mira; Chalabi, Nour El-Houda: Guided moth-flame optimiser for multi-objective optimization problems (2021)

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