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)

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  1. Cheng, Junheng; Chu, Feng; Chu, Chengbin; Xia, Weili: Bi-objective optimization of single-machine batch scheduling under time-of-use electricity prices (2016)
  2. Fliege, Jörg; Vaz, A.Ismael F.: A method for constrained multiobjective optimization based on SQP techniques (2016)
  3. Jornada, Daniel; Leon, V.Jorge: Biobjective robust optimization over the efficient set for Pareto set reduction (2016)
  4. Martin, Benjamin; Goldsztejn, Alexandre; Granvilliers, Laurent; Jermann, Christophe: On continuation methods for non-linear bi-objective optimization: towards a certified interval-based approach (2016)
  5. Schütze, Oliver; Martín, Adanay; Lara, Adriana; Alvarado, Sergio; Salinas, Eduardo; Coello Coello, Carlos A.: The directed search method for multi-objective memetic algorithms (2016)
  6. Cao, Yongtao; Smucker, Byran J.; Robinson, Timothy J.: On using the hypervolume indicator to compare Pareto fronts: applications to multi-criteria optimal experimental design (2015)
  7. Gallard, François; Mohammadi, Bijan; Montagnac, Marc; Meaux, Matthieu: An adaptive multipoint formulation for robust parametric optimization (2015)
  8. Ghosh, Debdas; Chakraborty, Debjani: A direction based classical method to obtain complete Pareto set of multi-criteria optimization problems (2015)
  9. Hartikainen, Markus E.; Lovison, Alberto: PAINT-SICon: constructing consistent parametric representations of Pareto sets in nonconvex multiobjective optimization (2015)
  10. Khaledian, Kazhal; Soleimani-damaneh, Majid: A new approach to approximate the bounded Pareto front (2015)
  11. Rubio-Largo, Álvaro; Zhang, Qingfu; Vega-Rodríguez, Miguel: Multiobjective evolutionary algorithm based on decomposition for 3-objective optimization problems with objectives in different scales (2015)
  12. Ruiz, Ana B.; Sindhya, Karthik; Miettinen, Kaisa; Ruiz, Francisco; Luque, Mariano: E-NAUTILUS: a decision support system for complex multiobjective optimization problems based on the NAUTILUS method (2015)
  13. Salazar, F.J.T.; Macau, E.E.N.; Winter, O.C.: Pareto frontier for the time-energy cost vector to an Earth-Moon transfer orbit using the patched-conic approximation (2015)
  14. Wang, Honggang: Direct zigzag search for discrete multi-objective optimization (2015)
  15. Abounacer, Rachida; Rekik, Monia; Renaud, Jacques: An exact solution approach for multi-objective location-transportation problem for disaster response (2014)
  16. Burachik, R.S.; Kaya, C.Y.; Rizvi, M.M.: A new scalarization technique to approximate Pareto fronts of problems with disconnected feasible sets (2014)
  17. Chow, Joseph Y.J.; Regan, Amelia C.: A surrogate-based multiobjective metaheuristic and network degradation simulation model for robust toll pricing (2014)
  18. García-Alonso, Carlos R.; Pérez-Naranjo, Leonor M.; Fernández-Caballero, Juan C.: Multiobjective evolutionary algorithms to identify highly autocorrelated areas: the case of spatial distribution in financially compromised farms (2014)
  19. Khorram, E.; Khaledian, K.; Khaledyan, M.: A numerical method for constructing the Pareto front of multi-objective optimization problems (2014)
  20. Qu, Shaojian; Liu, Chen; Goh, Mark; Li, Yijun; Ji, Ying: Nonsmooth multiobjective programming with quasi-Newton methods (2014)

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