BACKGROUND Honey bees are complex eusocial insects that provide a critical contribution to human agricultural food production. Their natural migration has selected for traits that increase fitness within geographical areas, but in parallel their domestication has selected for traits that enhance productivity and survival under local conditions. Elucidating the biochemical mechanisms of these lo...

This paper suggests a dynamic multi-colony multi-objective artificial bee colony algorithm (DMCMOABC) by using the multi-deme model and a dynamic information exchange strategy. In the proposed algorithm, K colonies search independently most of the time and share information occasionally. In each colony, there are S bees containing equal number of employed bees and onlooker bees. For each food s...

Artificial Bee Colony (ABC) is a swarm optimization technique. This algorithm generally used to solve nonlinear and complex problems. ABC is one of the simplest and up to date population based probabilistic strategy for global optimization. Analogous to other population based algorithms, ABC also has some drawbacks computationally pricey due to its sluggish temperament of search procedure. The ...

The multi-objective long-term economic dispatch in hydropower system is a complicated nonlinear optimization problem with a group of complex constraints which makes the optimization of conflict objectives through traditional methods a hard task. This paper is aim to present a novel multi-objective evolutionary algorithm named multiobjective artificial bee colony (MOABC) algorithm and compares t...

Eighty-eight percent of all 40-year-old male residents of four suburban municipalities of Copenhagen County were examined for the lead concentration in their blood and interviewed regarding job category and place of work. Of the 504 men, 482 were currently employed, 18 were unemployed, and 4 were pensioners. The total median blood lead level was 13 micrograms/100 ml (0.6 mumol/l). Men employed ...

In this paper the performance of four well-known metaheuristics consisting of Artificial Bee Colony (ABC), Biogeographic Based Optimization (BBO), Harmony Search (HS) and Teaching Learning Based Optimization (TLBO) are investigated on optimal domain decomposition for parallel computing. A clique graph is used for transforming the connectivity of a finite element model (FEM) into that of the cor...

The Artificial Bee Colony (ABC) algorithm recently gained high popularity by providing a robust and efficient approach for solving continuous optimization problems. In order to apply ABC in discrete landscape, a binary version of artificial bee colony (BABC) algorithm is proposed in this manuscript. Unlike the original ABC algorithm, the proposed BABC represents a food source as a discrete bina...

To date, exploring an efficient method for optimizing Least Squares Support Vector Machines (LSSVM) hyperparameters has been an enthusiastic research area among academic researchers. LSSVM is a practical machine learning approach that has been broadly utilized in numerous fields. To guarantee its convincing performance, it is crucial to select an appropriate technique in order to obtain the opt...

To solve the job shop scheduling problem with the objective of minimizing total weighted tardiness, an artificial bee colony algorithm based on problem data analysis is proposed. First, characteristic values are defined to describe the criticality of each job in the process of scheduling and optimization. Then, a fuzzy inference system is employed to evaluate the characteristic values according...

Meta-heuristic algorithms are applied in optimization problems in a variety of fields, including engineering, economics, and computer science. In this paper, seven population-based meta-heuristic algorithms are employed for size and geometry optimization of truss structures. These algorithms consist of the Artificial Bee Colony algorithm, Cyclical Parthenogenesis Algorithm, Cuckoo Search algori...