Multi-colony bacteria foraging optimization with cell-to-cell communication for RFID network planning

Evolução de filtros ótimos com algoritmo fireworks para análise por níveis de erro em imagens comprimidas com perdas

“…Seguindo o mesmo princípio básico, alguns algoritmos tem sido bem sucedidos em suas propostas e desenvolvimentos, inspirados por estes comportamentos coletivos e sociais de grupos como enxames de pássaros, cardumes de peixes ou enxames de insetos [13]; otimização por enxame de partículas (Particle Swarm Optimization -PSO) [14], otimização por colônia de formigas (Ant Colony Optimization -ACO) [15], colônia artificial de abelhas (Artificial Bee Colony -ABC) [16] e forrageamento de bactérias (Bacterial Foraging -BF) [17] são apenas alguns exemplos.…”

A Discrete Artificial Bee Colony Algorithm for RFID Network Scheduling

“…In this approach, readers with overlapping fields are fired at different times so that they do not collide. Both of these allocations (spectral and temporal) can be modeled as graph partitioning problems (GPP) [5].…”

“…This result in an unacceptable level of misreads. The main feature of anti-collision approach is that the interference is solved by frequency assignment [4]and reader scheduling 5 , which extract techniques started with the application of graph theoretic tools to the problem of assigning radio frequency spectrum to a set of radio frequency transmitters, such as cellular telephone base stations. The other method of collision avoidance is time scheduling.…”

Bacterial colony foraging optimization

“…Three improved versions of BFO, namely the cooperative bacterial foraging optimizer (CBFO), adaptive bacterial optimization, and multicolony bacterial foraging optimization (MCBFO), have been described in our previous works [29,30,34]. In [29], instead of simply considering chemotaxis behavior of single bacterium, MCBFO also introduced the communication strategies employs by natural multi-colony bacterial community in order to coordinate pattern emerges, which is lacking from the mentioned chemotaxis inspired algorithms.…”

“…In [29], instead of simply considering chemotaxis behavior of single bacterium, MCBFO also introduced the communication strategies employs by natural multi-colony bacterial community in order to coordinate pattern emerges, which is lacking from the mentioned chemotaxis inspired algorithms. Then the MCBFO was evaluated on the static RFID network planning problem in comparison with GA and PSO.…”