Honey Bee Mating Optimization (HBMO) is a recent swarm-based optimization algorithm to solve highly nonlinear problems, whose based approach combines the powers of simulated annealing, genetic algorithms, and an effective local search heuristic to search for the best possible solution to the problem under investigation within a reasonable computing time. In this work, the HBMO-based design is c...

A Honey Bee Mating Optimization (HBMO) technique is proposed for the optimal tuning of the Power System Stabilizer (PSS) in this paper. The design problem of robustly selecting PSS parameters is formulated as an optimization problem according to the time domain-based objective function which is solved by the HBMO technique that has a strong ability to find the most optimistic results. To achiev...

This paper introduces a new hybrid algorithmic nature inspired approach based on the concepts of the Honey Bees Mating Optimization Algorithm (HBMO) and of the Greedy Randomized Adaptive Search Procedure (GRASP), for optimally clustering N objects into K clusters. The proposed algorithm for the Clustering Analysis, the Hybrid HBMO-GRASP, is a two phase algorithm which combines a HBMO algorithm ...

As a nonlinear, non-convex and large scale optimization problem including both continuous and discrete control variables, security-constrained optimal power flow (SC-OPF) is one of the most important power system problems which need a superior optimization technique to be effectively solved. Inspired by the mating process of honey bees, honey bee mating optimization (HBMO) is a recently invente...

The minimum cross entropy thresholding (MCET) has been widely applied in image processing. In this paper, a new multilevel MCET algorithm based on the artificial bee colony (ABC) algorithm is proposed. The proposed thresholding algorithm is called ABC-based MCET algorithm. Four different methods including the exhaustive search, the honey bee mating optimization (HBMO), the particle swarm optimi...

Image entropy thresholding approach has drawn the attentions in image segmatation. The endeavor of this paper is focused on multilevel thresholding using the minimum cross enrtop criterion. In the literature, the particle swarm optimization (PSO) had been applied to conducting the thresold selection. The adopted algorithm used in this paper is the honey bee mating optimization (HBMO). In experi...

mobile ad hoc networks (manets) are composed of mobile stations communicating through wireless links, without any fixed backbone support. in these networks, limited power energy supply, and frequent topology changes caused by node mobility, makes their routing a challenging problem. tora is one of the routing protocols that successfully copes with the nodes’ mobility side effects, but it doesn’...

In this paper, a new approach based on the Honey bee mating optimization (HBMO) technique is proposed to tune the parameters of the multi-machine power system stabilizers (PSSs). The honey-bee mating process has been considered as a typical swarm-based approach to optimization, in which the search algorithm is inspired by the process of real honey-bee mating. The PSSs parameters tuning problem ...