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Multi-Objective Optimization Using Evolutionary Algorithms
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Evolutionary Computation
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Proceedings of the 10th annual conference on Genetic and evolutionary computation
Reference Point-Based Particle Swarm Optimization Using a Steady-State Approach
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Advances in Engineering Software
Expert Systems with Applications: An International Journal
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Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
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International Journal of Innovative Computing and Applications
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Evolutionary Computation
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Applied Intelligence
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Natural Computing: an international journal
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ICIC'10 Proceedings of the 6th international conference on Advanced intelligent computing theories and applications: intelligent computing
Structural and Multidisciplinary Optimization
On convergence of the multi-objective particle swarm optimizers
Information Sciences: an International Journal
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Winter Simulation Conference
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ICSI'11 Proceedings of the Second international conference on Advances in swarm intelligence - Volume Part II
A modified multi-objective binary particle swarm optimization algorithm
ICSI'11 Proceedings of the Second international conference on Advances in swarm intelligence - Volume Part II
ICSI'11 Proceedings of the Second international conference on Advances in swarm intelligence - Volume Part II
Optimization of UPFCs using hierarchical multi-objective optimization algorithms
Analog Integrated Circuits and Signal Processing
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Applied Soft Computing
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KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part III
Multi-objective blind image fusion
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Multi-objective PSO algorithm based on fitness sharing and online elite archiving
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
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Multi-objective particle swarm optimization based on minimal particle angle
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part I
Genetic Programming and Evolvable Machines
Information Sciences: an International Journal
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SEMCCO'11 Proceedings of the Second international conference on Swarm, Evolutionary, and Memetic Computing - Volume Part I
A hybrid multiobjective evolutionary algorithm: Striking a balance with local search
Mathematical and Computer Modelling: An International Journal
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Mathematical and Computer Modelling: An International Journal
Expert Systems with Applications: An International Journal
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Improved MOPSO based on ε-domination
ICIC'12 Proceedings of the 8th international conference on Intelligent Computing Theories and Applications
Multi-Objective particle swarm optimization algorithm based on differential populations
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Handling multi-optimization with gender-hierarchy based particle swarm optimizer
ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part I
ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part I
Task allocation in distributed computing systems using adaptive particle swarm optimisation
International Journal of Computer Applications in Technology
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Artificial Life and Robotics
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Movement Strategies for Multi-Objective Particle Swarm Optimization
International Journal of Applied Metaheuristic Computing
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Cooperative particle swarm optimization for multiobjective transportation planning
Applied Intelligence
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International Journal of Computing Science and Mathematics
Engineering Applications of Artificial Intelligence
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This paper introduces a modified PSO, Non-dominated Sorting Particle Swarm Optimizer (NSPSO), for better multiobjective optimization. NSPSO extends the basic form of PSO by making a better use of particles' personal bests and offspring for more effective nondomination comparisons. Instead of a single comparison between a particle's personal best and its offspring, NSPSO compares all particles' personal bests and their offspring in the entire population. This proves to be effective in providing an appropriate selection pressure to propel the swarm population towards the Pareto-optimal front. By using the non-dominated sorting concept and two parameter-free niching methods, NSPSO and its variants have shown remarkable performance against a set of well-known difficult test functions (ZDT series). Our results and comparison with NSGA II show that NSPSO is highly competitive with existing evolutionary and PSO multiobjective algorithms.