Computational geometry: an introduction
Computational geometry: an introduction
Some algorithms based on the dual of Dilworth's theorem
Science of Computer Programming
The art of computer programming, volume 1 (3rd ed.): fundamental algorithms
The art of computer programming, volume 1 (3rd ed.): fundamental algorithms
SODA '93 Proceedings of the fourth annual ACM-SIAM Symposium on Discrete algorithms
On Finding the Maxima of a Set of Vectors
Journal of the ACM (JACM)
Output-size sensitive algorithms for finding maximal vectors
SCG '85 Proceedings of the first annual symposium on Computational geometry
Multidimensional divide-and-conquer
Communications of the ACM
Multidimensional binary search trees used for associative searching
Communications of the ACM
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Proceedings of the 17th International Conference on Data Engineering
Efficient Progressive Skyline Computation
Proceedings of the 27th International Conference on Very Large Data Bases
Exact Asymptotics of Divide-and-Conquer Recurrences
ICALP '93 Proceedings of the 20th International Colloquium on Automata, Languages and Programming
Enumerating extreme points in higher dimensions
Nordic Journal of Computing
Scaling and related techniques for geometry problems
STOC '84 Proceedings of the sixteenth annual ACM symposium on Theory of computing
Three-Dimensional Layers of Maxima
Algorithmica
Progressive skyline computation in database systems
ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2003
Approximating the Nondominated Front Using the Pareto Archived Evolution Strategy
Evolutionary Computation
Comparison of Multiobjective Evolutionary Algorithms: Empirical Results
Evolutionary Computation
Multicriteria Optimization
Random Structures & Algorithms
Algorithms and analyses for maximal vector computation
The VLDB Journal — The International Journal on Very Large Data Bases
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Shooting stars in the sky: an online algorithm for skyline queries
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Muiltiobjective optimization using nondominated sorting in genetic algorithms
Evolutionary Computation
More output-sensitive geometric algorithms
SFCS '94 Proceedings of the 35th Annual Symposium on Foundations of Computer Science
Efficient sort-based skyline evaluation
ACM Transactions on Database Systems (TODS)
Multiobjective optimization problems with complicated Pareto sets, MOEA/D and NSGA-II
IEEE Transactions on Evolutionary Computation
Reverse skyline search in uncertain databases
ACM Transactions on Database Systems (TODS)
In-Place Algorithms for Computing (Layers of) Maxima
Algorithmica - Including a Special Section on Genetic and Evolutionary Computation; Guest Editors: Benjamin Doerr, Frank Neumann and Ingo Wegener
A new data structure for the nondominance problem in multi-objective optimization
EMO'03 Proceedings of the 2nd international conference on Evolutionary multi-criterion optimization
Random Structures & Algorithms
Evolutionary multi-objective optimization: a historical view of the field
IEEE Computational Intelligence Magazine
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Using unconstrained elite archives for multiobjective optimization
IEEE Transactions on Evolutionary Computation
Reducing the run-time complexity of multiobjective EAs: The NSGA-II and other algorithms
IEEE Transactions on Evolutionary Computation
| Hi-index | 0.00 |
Simple, two-phase algorithms are devised for finding the maxima of multidimensional point samples, one of the very first problems studied in computational geometry. The algorithms are easily coded and modified for practical needs. The expected complexity of some measures related to the performance of the algorithms is analyzed. We also compare the efficiency of the algorithms with a few major ones used in practice, and apply our algorithms to find the maximal layers and the longest common subsequences of multiple sequences.