An upgraded firefly algorithm with feasibility-based rules for constrained engineering optimization problems
Published 2018 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
An upgraded firefly algorithm with feasibility-based rules for constrained engineering optimization problems
Authors
Keywords
Firefly algorithm, Engineering optimization, Constrained optimization, Nature-inspired algorithms
Journal
JOURNAL OF INTELLIGENT MANUFACTURING
Volume -, Issue -, Pages -
Publisher
Springer Nature
Online
2018-04-02
DOI
10.1007/s10845-018-1419-6
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- A novel differential evolution algorithm for solving constrained engineering optimization problems
- (2017) Ali Wagdy Mohamed JOURNAL OF INTELLIGENT MANUFACTURING
- Moth-flame optimization algorithm to determine optimal machining parameters in manufacturing processes
- (2017) Betül Sultan Yıldız et al. Materials Testing
- Passing vehicle search (PVS): A novel metaheuristic algorithm
- (2016) Poonam Savsani et al. APPLIED MATHEMATICAL MODELLING
- Improved accelerated PSO algorithm for mechanical engineering optimization problems
- (2016) Najeh Ben Guedria APPLIED SOFT COMPUTING
- A novel metaheuristic method for solving constrained engineering optimization problems: Crow search algorithm
- (2016) Alireza Askarzadeh COMPUTERS & STRUCTURES
- A new optimization algorithm for solving complex constrained design optimization problems
- (2016) R. Venkata Rao et al. ENGINEERING OPTIMIZATION
- Engineering optimization based on ideal gas molecular movement algorithm
- (2016) Hesam Varaee et al. ENGINEERING WITH COMPUTERS
- Engineering design optimization using an improved local search based epsilon differential evolution algorithm
- (2016) Wenchao Yi et al. JOURNAL OF INTELLIGENT MANUFACTURING
- Parallel chaotic local search enhanced harmony search algorithm for engineering design optimization
- (2016) Jin Yi et al. JOURNAL OF INTELLIGENT MANUFACTURING
- Modified firefly algorithm for multidimensional optimization in structural design problems
- (2016) Jui-Sheng Chou et al. STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
- A Novel Hybrid Firefly Algorithm for Global Optimization
- (2016) Lina Zhang et al. PLoS One
- A review of chaos-based firefly algorithms: Perspectives and research challenges
- (2015) Iztok Fister et al. APPLIED MATHEMATICS AND COMPUTATION
- Adaptive firefly algorithm with chaos for mechanical design optimization problems
- (2015) Adil Baykasoğlu et al. APPLIED SOFT COMPUTING
- A new modification approach on bat algorithm for solving optimization problems
- (2015) Selim Yılmaz et al. APPLIED SOFT COMPUTING
- Crossover-based artificial bee colony algorithm for constrained optimization problems
- (2015) Ivona Brajevic NEURAL COMPUTING & APPLICATIONS
- Grey Wolf Optimizer
- (2014) Seyedali Mirjalili et al. ADVANCES IN ENGINEERING SOFTWARE
- Symbiotic Organisms Search: A new metaheuristic optimization algorithm
- (2014) Min-Yuan Cheng et al. COMPUTERS & STRUCTURES
- Self-adaptive mix of particle swarm methodologies for constrained optimization
- (2014) Saber M. Elsayed et al. INFORMATION SCIENCES
- Multiobjective optimization of torch brazing process by a hybrid of fuzzy logic and multiobjective artificial bee colony algorithm
- (2014) Alejandro Alvarado-Iniesta et al. JOURNAL OF INTELLIGENT MANUFACTURING
- An improved teaching-learning-based optimization algorithm for numerical and engineering optimization problems
- (2014) Kunjie Yu et al. JOURNAL OF INTELLIGENT MANUFACTURING
- True global optimality of the pressure vessel design problem: a benchmark for bio-inspired optimisation algorithms
- (2014) Xin She Yang et al. International Journal of Bio-Inspired Computation
- Exploration and exploitation in evolutionary algorithms
- (2013) Matej Črepinšek et al. ACM COMPUTING SURVEYS
- A review on particle swarm optimization algorithm and its variants to clustering high-dimensional data
- (2013) Ahmed A. A. Esmin et al. ARTIFICIAL INTELLIGENCE REVIEW
- Engineering optimization by means of an improved constrained differential evolution
- (2013) Wenyin Gong et al. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
- A framework for self-tuning optimization algorithm
- (2013) Xin-She Yang et al. NEURAL COMPUTING & APPLICATIONS
- A comprehensive review of firefly algorithms
- (2013) Iztok Fister et al. Swarm and Evolutionary Computation
- Empirical analysis of a modified Artificial Bee Colony for constrained numerical optimization
- (2012) Efrén Mezura-Montes et al. APPLIED MATHEMATICS AND COMPUTATION
- Mine blast algorithm: A new population based algorithm for solving constrained engineering optimization problems
- (2012) Ali Sadollah et al. APPLIED SOFT COMPUTING
- A comprehensive survey: artificial bee colony (ABC) algorithm and applications
- (2012) Dervis Karaboga et al. ARTIFICIAL INTELLIGENCE REVIEW
- Firefly algorithm with chaos
- (2012) A.H. Gandomi et al. Communications in Nonlinear Science and Numerical Simulation
- Water cycle algorithm – A novel metaheuristic optimization method for solving constrained engineering optimization problems
- (2012) Hadi Eskandar et al. COMPUTERS & STRUCTURES
- Comparison of evolutionary-based optimization algorithms for structural design optimization
- (2012) Ali R. Yildiz ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- Multiobjective firefly algorithm for continuous optimization
- (2012) Xin-She Yang ENGINEERING WITH COMPUTERS
- Investigating Multi-View Differential Evolution for solving constrained engineering design problems
- (2012) Vinícius V. de Melo et al. EXPERT SYSTEMS WITH APPLICATIONS
- Constrained optimization based on modified differential evolution algorithm
- (2012) Ali Wagdy Mohamed et al. INFORMATION SCIENCES
- An upgraded artificial bee colony (ABC) algorithm for constrained optimization problems
- (2012) Ivona Brajevic et al. JOURNAL OF INTELLIGENT MANUFACTURING
- Evolutionary boundary constraint handling scheme
- (2012) Amir Hossein Gandomi et al. NEURAL COMPUTING & APPLICATIONS
- Bat algorithm for constrained optimization tasks
- (2012) Amir Hossein Gandomi et al. NEURAL COMPUTING & APPLICATIONS
- Teaching–learning-based optimization: A novel method for constrained mechanical design optimization problems
- (2011) R.V. Rao et al. COMPUTER-AIDED DESIGN
- Multi-operator based evolutionary algorithms for solving constrained optimization problems
- (2011) Saber M. Elsayed et al. COMPUTERS & OPERATIONS RESEARCH
- Mixed variable structural optimization using Firefly Algorithm
- (2011) Amir Hossein Gandomi et al. COMPUTERS & STRUCTURES
- Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems
- (2011) Amir Hossein Gandomi et al. ENGINEERING WITH COMPUTERS
- Constraint-handling in nature-inspired numerical optimization: Past, present and future
- (2011) Efrén Mezura-Montes et al. Swarm and Evolutionary Computation
- A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms
- (2011) Joaquín Derrac et al. Swarm and Evolutionary Computation
- A modified Artificial Bee Colony (ABC) algorithm for constrained optimization problems
- (2010) Dervis Karaboga et al. APPLIED SOFT COMPUTING
- Ensemble of Constraint Handling Techniques
- (2010) R Mallipeddi et al. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
- Artificial bee colony algorithm for large-scale problems and engineering design optimization
- (2010) Bahriye Akay et al. JOURNAL OF INTELLIGENT MANUFACTURING
- Firefly algorithm, stochastic test functions and design optimisation
- (2010) Xin She Yang International Journal of Bio-Inspired Computation
- Hybridizing particle swarm optimization with differential evolution for constrained numerical and engineering optimization
- (2009) Hui Liu et al. APPLIED SOFT COMPUTING
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExplorePublish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn More