Binary artificial bee colony optimization

A micro-artificial bee colony based multicast routing in vehicular ad hoc networks

“…It is recently extended to handle combinational optimization problems [26,27] . The colony of ABC is comprised by employed bees, onlooker bees, and scout bees.…”

A binary ABC algorithm based on advanced similarity scheme for feature selection

“…The other goal is to put forward a comprehensive comparative study of some variants of the ABC, PSO and GA algorithms on wrapper feature selection in terms of the classification performance and the feature subset size for the future studies of researchers. To establish the second goal, seven algorithms, which are binary PSO (BPSO) [22], new velocity based binary PSO (NBPSO) [23], quantum inspired binary PSO (QBPSO) [24], discrete ABC (DisABC) [21], angle modulated ABC (AMABC) [25], modification rate based ABC (MRABC) [26] and genetic algorithms (GA) [27] are employed, and 10 benchmark datasets, including various classes, instances and features are chosen from the UCI machine learning repository [28]. To our knowledge, the employed algorithms except for BPSO and GA are the first time to be used in feature selection, and a comprehensive comparative analysis on feature selection is not very common in the literature.…”

“…Englebrecht [25] proposed a binary artificial bee algorithm inspired by angle modulation (AMABC). In AMABC, each candidate is represented via four dimensional continuous vector (a, b, c, d) within [−1, 1] and each candidate is transformed into a D-dimensional binary space by the sinusoid function.…”

Binary Bat Algorithm: On The Efficiency of Mapping Functions When Handling Binary Problems Using Continuous-variable-based Metaheuristics

“…Normalisation : This approach was proposed in [9,10]. It consists of the normalisation of the solution by linearaly scaling it using the Formula 14.…”