… bat algorithm with the direction of mean best position (QMBA). In QMBA, the position of each
bat is mainly updated by the current optimal … depends on the mean best position which can …

… However, the QMBA algorithm generates all stochastic … help bats escape from the local
optimum, this article proposes a novel Gaussian quantum bat algorithm with mean best position …

… KMBA, the KM and Bat Algorithm (BA) based on the echolocation behaviour of bats to
identify the initial values for overcome the KM issues. The algorithm does not require the user to …

… Bat algorithm (BA) is one of the recently proposed heuristic algorithms imitating the echolocation
behavior of bats to … However, the meaning of position updating is different in a discrete …

… 0 and 1, and At is the average loudness of all the bats at this step. … bat algorithm we aim
to find the most feasible or an improved solution for a particular QAP instance. Bat algorithm …

… Bat algorithm (BA) is a recent optimization algorithm based on swarm intelligence and
inspiration from the echolocation behavior of bats. … with a new definition of the bats’ movements. …

… = 0 and f max ≥ 1, BA will, on average, take larger steps than … best position a fraction of the
time equal to [1 − 1/(4f max )]. This also means that BA overshoots the global best position by …

… Bat algorithm for the node localization problem, the effectiveness of which is based on the
adaptation of velocity of the Bats by … When we analyze the Table 3A, we remark that mean …

… a complex-valued bat algorithm where each bat is coded in … learning (OBL) strategy into
bat algorithm. The opposite … the swarm historical best position with the mean best position to …

… algorithm combining the bat algorithm and the divide-and-conquer strategy. First, based
on the classical BA, the Gaussian quantum bat algorithm with direction of mean best position (…