Loading pattern optimization of PWR reactors using Artificial Bee Colony

Pattern optimization of PWR reactor using hybrid parallel Artificial Bee Colony

“…The performance of ABC had already been compared with other search optimization techniques such as genetic and particle swarm intelligence algorithms (Safarzadeh et al, 2011). The comparison results showed that ABC can find a better solution, and is more effective than mentioned optimization techniques.…”

“…Several algorithms have been developed and successfully applied to optimize reactor core loading problem such as Dynamic Programming (Wall and Fenech, 1965), direct search (Stout, 1973), Variational Techniques (Terney and Williamson, 1982), Backward Diffusion Calculation (Chao et al, 1986), Reverse Depletion (Downar and Kim, 1986;Kim et al, 1987), Linear Programming (Stillman et al, 1989), Simulated Annealing (Stevens, 1995), Ant Colony algorithm (Schirru et al, 2006), Safarzadeh et al (2011) applied ABC algorithm to power flattening of PWR reactor, continuous Genetic Algorithm (GA) introduced for flatting power distribution (Zolfaghari et al, 2009;Norouzi et al, 2011), discrete PSO (Babazadeh et al, 2009), continuous PSO (Khoshahval et al, 2010), Mohseni et al used GA in multi-objective optimization of lowering power peaking factor, maximization of the effective multiplication factor (Mohseni et al, 2008), Cellular Automata for maximizing initial excess reactivity and minimizing power peaking factor , Perturbation Theory (Stacey, 1974;Hosseini and Vosoughi, 2012), ArtificialIntelligence techniques like Artificial Neural Networks (ANNs) (Sadighi et al, 2002), and combination of fuzzy logic and ANN (Kim et al, 1993) are the ones most commonly used in core fuel management. A further study based on hybrid algorithms was performed (Stevens, 1995;Erdog and Geçkinli, 2003;).…”

MOF: A Modular Framework for Rapid Application of Optimization Methodologies to General Engineering Design Problems

“…Genetic algorithms (GA) and other evolutionary algorithms mimic the processes observed through the theory of evolution [5]. Other algorithms, such as artificial bee colonies or ant colony methods, replicate a very specific system from nature [6,7]. The Tabu search provides an example of an optimization methodology based on an internal logic.…”

A review on Artificial Bee Colony algorithm

“…Safarzadeh et al utilized ABC for loading pattern optimization of power reactors [49]. In this work, a core reloading technique using ABC was presented in the context of finding an optimal configuration of fuel assemblies.…”