Xiang et al., 2015 - Google Patents
An elitism based multi-objective artificial bee colony algorithmXiang et al., 2015
- Document ID
- 18123375715320259853
- Author
- Xiang Y
- Zhou Y
- Liu H
- Publication year
- Publication venue
- European Journal of Operational Research
External Links
Snippet
In this paper, we suggest a new multi-objective artificial bee colony (ABC) algorithm by introducing an elitism strategy. The algorithm uses a fixed-size archive that is maintained based on crowding-distance to store non-dominated solutions found during the search …
- 238000004422 calculation algorithm 0 title abstract description 144
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/12—Computer systems based on biological models using genetic models
- G06N3/126—Genetic algorithms, i.e. information processing using digital simulations of the genetic system
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
- G06F17/30386—Retrieval requests
- G06F17/30424—Query processing
- G06F17/30533—Other types of queries
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30943—Information retrieval; Database structures therefor; File system structures therefor details of database functions independent of the retrieved data type
- G06F17/30946—Information retrieval; Database structures therefor; File system structures therefor details of database functions independent of the retrieved data type indexing structures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/02—Knowledge representation
- G06N5/022—Knowledge engineering, knowledge acquisition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/04—Inference methods or devices
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/12—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for modelling or simulation in systems biology, e.g. probabilistic or dynamic models, gene-regulatory networks, protein interaction networks or metabolic networks
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Xiang et al. | An elitism based multi-objective artificial bee colony algorithm | |
Cui et al. | A ranking-based adaptive artificial bee colony algorithm for global numerical optimization | |
Tiwari et al. | AMGA2: improving the performance of the archive-based micro-genetic algorithm for multi-objective optimization | |
Panagant et al. | Truss topology, shape and sizing optimization by fully stressed design based on hybrid grey wolf optimization and adaptive differential evolution | |
Ning et al. | Constrained multi-objective optimization using constrained non-dominated sorting combined with an improved hybrid multi-objective evolutionary algorithm | |
Taboada et al. | Practical solutions for multi-objective optimization: An application to system reliability design problems | |
Chen et al. | A hybrid immune multiobjective optimization algorithm | |
Wang et al. | An Improved Hybrid Algorithm Based on Biogeography/Complex and Metropolis for Many‐Objective Optimization | |
Icke et al. | Improving genetic programming based symbolic regression using deterministic machine learning | |
Santiago et al. | A survey of decomposition methods for multi-objective optimization | |
Yar et al. | A survey on evolutionary computation: Methods and their applications in engineering | |
Shin et al. | Multi-objective FMS process planning with various flexibilities using a symbiotic evolutionary algorithm | |
Zhang et al. | Dynamic multiscale region search algorithm using vitality selection for traveling salesman problem | |
Chen et al. | Modified differential evolution algorithm using a new diversity maintenance strategy for multi-objective optimization problems | |
Zhong et al. | A multi-objective artificial bee colony algorithm based on division of the searching space | |
Chen et al. | Application of novel clonal algorithm in multiobjective optimization | |
Bandyopadhyay et al. | Incorporating ϵ-dominance in AMOSA: Application to multiobjective 0/1 knapsack problem and clustering gene expression data | |
Wang et al. | Improved NSGA-II algorithm for optimization of constrained functions | |
Sharma et al. | Power law-based local search in artificial bee colony | |
Doush et al. | Hybedrized nsga-ii and moea/d with harmony search algorithm to solve multi-objective optimization problems | |
Wang et al. | Multiobjective optimization algorithm with objective-wise learning for continuous multiobjective problems | |
Chen et al. | Chaotic differential evolution algorithm for resource constrained project scheduling problem | |
Pan et al. | A Decomposition‐Based Unified Evolutionary Algorithm for Many‐Objective Problems Using Particle Swarm Optimization | |
Jin et al. | Adaptive, convergent, and diversified archiving strategy for multiobjective evolutionary algorithms | |
Ali et al. | Balancing search direction in cultural algorithm for enhanced global numerical optimization |