An efficient approach to unbounded bi-objective archives -: introducing the mak_tree algorithm
Proceedings of the 8th annual conference on Genetic and evolutionary computation
An efficient multi-objective evolutionary algorithm with steady-state replacement model
Proceedings of the 8th annual conference on Genetic and evolutionary computation
MOCDEX: multiprocessor on chip multiobjective design space exploration with direct execution
EURASIP Journal on Embedded Systems
AMGA: an archive-based micro genetic algorithm for multi-objective optimization
Proceedings of the 10th annual conference on Genetic and evolutionary computation
An efficient non-dominated sorting method for evolutionary algorithms
Evolutionary Computation
F-score with Pareto Front Analysis for Multiclass Gene Selection
EvoBIO '09 Proceedings of the 7th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
EMO '09 Proceedings of the 5th International Conference on Evolutionary Multi-Criterion Optimization
EMO '09 Proceedings of the 5th International Conference on Evolutionary Multi-Criterion Optimization
Non-even spread NSGA-II and its application to conflicting multi-objective compatible control
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
A dominance tree and its application in evolutionary multi-objective optimization
Information Sciences: an International Journal
IEEE Transactions on Evolutionary Computation - Special issue on computational finance and economics
IEEE Transactions on Wireless Communications
A fast multi-objective evolutionary algorithm based on a tree structure
Applied Soft Computing
Statistical methods for convergence detection of multi-objective evolutionary algorithms
Evolutionary Computation
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Expert Systems with Applications: An International Journal
Pareto-, aggregation-, and indicator-based methods in many-objective optimization
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
Combining mapping and partitioning exploration for NoC-based embedded systems
Journal of Systems Architecture: the EUROMICRO Journal
Information Sciences: an International Journal
The r-dominance: a new dominance relation for interactive evolutionary multicriteria decision making
IEEE Transactions on Evolutionary Computation - Special issue on preference-based multiobjective evolutionary algorithms
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
A hybrid TP+PLS algorithm for bi-objective flow-shop scheduling problems
Computers and Operations Research
A fast steady-state ε-dominance multi-objective evolutionary algorithm
Computational Optimization and Applications
Using an adaptation of a binary search tree to improve the NSGA-II nondominated sorting procedure
SEAL'10 Proceedings of the 8th international conference on Simulated evolution and learning
Variable preference modeling using multi-objective evolutionary algorithms
EMO'11 Proceedings of the 6th international conference on Evolutionary multi-criterion optimization
Maxima-finding algorithms for multidimensional samples: A two-phase approach
Computational Geometry: Theory and Applications
A fast and effective method for pruning of non-dominated solutions in many-objective problems
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Omni-optimizer: a procedure for single and multi-objective optimization
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
The combative accretion model – multiobjective optimisation without explicit pareto ranking
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Deductive sort and climbing sort: New methods for non-dominated sorting
Evolutionary Computation
A novel non-dominated sorting algorithm
SEMCCO'11 Proceedings of the Second international conference on Swarm, Evolutionary, and Memetic Computing - Volume Part I
Computer Networks: The International Journal of Computer and Telecommunications Networking
BSTBGA: A hybrid genetic algorithm for constrained multi-objective optimization problems
Computers and Operations Research
Multi-objective path planning in discrete space
Applied Soft Computing
A Scheduling Model with Multi-Objective Optimization for Computational Grids using NSGA-II
International Journal of Applied Evolutionary Computation
Attempt to reduce the computational complexity in multi-objective differential evolution algorithms
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Generalizing the improved run-time complexity algorithm for non-dominated sorting
Proceedings of the 15th annual conference on Genetic and evolutionary computation
The asynchronous island model and NSGA-II: study of a new migration operator and its performance
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Applying modified NSGA-II for bi-objective supply chain problem
Journal of Intelligent Manufacturing
Pareto Optimal Pairwise Sequence Alignment
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Non-additive multi-objective robot coalition formation
Expert Systems with Applications: An International Journal
Optimization of electrospinning process using intelligent control systems
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Recent Advances in Soft Computing: Theories and Applications
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The last decade has seen a surge of research activity on multiobjective optimization using evolutionary computation and a number of well performing algorithms have been published. The majority of these algorithms use fitness assignment based on Pareto-domination: Nondominated sorting, dominance counting, or identification of the nondominated solutions. The success of these algorithms indicates that this type of fitness is suitable for multiobjective problems, but so far the use of Pareto-based fitness has lead to program run times in O(GMN2), where G is the number of generations, M is the number of objectives, and N is the population size. The N2 factor should be reduced if possible, since it leads to long processing times for large population sizes. This paper presents a new and efficient algorithm for nondominated sorting, which can speed up the processing time of some multiobjective evolutionary algorithms (MOEAs) substantially. The new algorithm is incorporated into the nondominated sorting genetic algorithm II (NSGA-II) and reduces the overall run-time complexity of this algorithm to O(GN logM-1N), much faster than the O(GMN2) complexity published by Deb et al. (2002). Experiments demonstrate that the improved version of the algorithm is indeed much faster than the previous one. The paper also points out that multiobjective EAs using fitness based on dominance counting and identification of nondominated solutions can be improved significantly in terms of running time by using efficient algorithms known from computer science instead of inefficient O(MN2) algorithms.