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. 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)
  2. Burachik, R.S.; Kaya, C.Y.; Rizvi, M.M.: A new scalarization technique and new algorithms to generate Pareto fronts (2017)
  3. Cao, Yongtao; Smucker, Byran J.; Robinson, Timothy J.: A hybrid elitist Pareto-based coordinate exchange algorithm for constructing multi-criteria optimal experimental designs (2017)
  4. 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)
  5. 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)
  6. Sánchez, Helem Sabina; Visioli, Antonio; Vilanova, Ramon: Optimal Nash tuning rules for robust PID controllers (2017)
  7. Cheng, Junheng; Chu, Feng; Chu, Chengbin; Xia, Weili: Bi-objective optimization of single-machine batch scheduling under time-of-use electricity prices (2016)
  8. Fliege, Jörg; Vaz, A.Ismael F.: A method for constrained multiobjective optimization based on SQP techniques (2016)
  9. Jornada, Daniel; Leon, V.Jorge: Biobjective robust optimization over the efficient set for Pareto set reduction (2016)
  10. Martin, Benjamin; Goldsztejn, Alexandre; Granvilliers, Laurent; Jermann, Christophe: On continuation methods for non-linear bi-objective optimization: towards a certified interval-based approach (2016)
  11. Nowé, Ann; Brys, Tim: A gentle introduction to reinforcement learning (2016)
  12. Schütze, Oliver; Martín, Adanay; Lara, Adriana; Alvarado, Sergio; Salinas, Eduardo; Coello Coello, Carlos A.: The directed search method for multi-objective memetic algorithms (2016)
  13. 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)
  14. De Faria, Alfredo R.: Optimization of composite structures under multiple load cases using a discrete approach based on lamination parameters (2015)
  15. Gallard, François; Mohammadi, Bijan; Montagnac, Marc; Meaux, Matthieu: An adaptive multipoint formulation for robust parametric optimization (2015)
  16. Ghosh, Debdas; Chakraborty, Debjani: A direction based classical method to obtain complete Pareto set of multi-criteria optimization problems (2015)
  17. Hartikainen, Markus E.; Lovison, Alberto: PAINT-SICon: constructing consistent parametric representations of Pareto sets in nonconvex multiobjective optimization (2015)
  18. Khaledian, Kazhal; Soleimani-damaneh, Majid: A new approach to approximate the bounded Pareto front (2015)
  19. 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) ioport
  20. 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)

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