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...

The Varroa mite has many deleterious impacts on honey bee colonies. These impacts are well known and include, for example, the weakness of honey bees by feeding on the haemolymph (Rosenkranz et al. 2010), transportation of viruses to host bees including Kashmir bee virus (Chen et al. 2004), suppresses the immunity of honey bees (Shen et al. 2005), impact bee wing Shape (Cakmak et al. 2011) and ...

Tuning of the system and the controller parameters always constituted an important part of the control applications in power system. These processes need complex mathematical calculations including derivative elements classically. However, these nowadays accomplished more easily and in shorter times, using by iterative optimization approaches such as evolutionary or swarm intelligence based met...

In this paper, a constrained mean-variance model is constructed for the portfolio optimization problems. The model is a mixed quadratic integer programming problem, and it is too hard to solve by using the traditional optimal algorithms. The purpose of this paper is to use a heuristic algorithm to solve this problem. Combined with the differential evolution strategy, a new hybrid artificial bee...

Bio inspiration is a branch of artificial simulation science that shows pervasive contributions to variety of engineering fields such as automate pattern recognition, systematic fault detection and applied optimization. In this paper, a new metaheuristic optimizing algorithm that is the simulation of “The Great Salmon Run” (TGSR) is developed. The obtained results imply on the acceptable perfor...

Research on distributed task planning model for multi-autonomous underwater vehicle (MAUV). A scroll time domain quantum artificial bee colony (STDQABC) optimization algorithm is proposed to solve the multi-AUV optimal task planning scheme. In the uncertain marine environment, the rolling time domain control technique is used to realize a numerical optimization in a narrowed time range. Rolling...

Non-random mating in plant populations can be influenced by numerous reproductive and demographic factors, including floral morphology and inter-plant distance. Here, we investigate patterns of outcrossed mating through male function in Narcissus triandrus, a tristylous, bee-pollinated wild daffodil from the Iberian Peninsula, to test pollen transfer models which predict that floral morphology ...

Bee colony optimization (BCO) is one of the most recent algorithms in swarm intelligence that can be used in optimization problems this algorithm is based on the intelligent behavior of honey bees in foraging process. In this paper bee colony optimization is applied to solve the task scheduling problem which tasks have dependency with each other. Scheduling of tasks that represents by directed ...

This paper empirically evaluates four meta-heuristic search techniques namely particle swarm optimization, artificial bee colony algorithm, Genetic Algorithm and Big Bang Big Crunch Algorithm for automatic test data generation for procedure oriented programs using structural symbolic testing method. Test data is generated for each feasible path of the programs. Experiments on ten benchmark prog...

Artificial bee colony (ABC) is a relatively new swarm intelligence based metaheuristic. It was successfully applied to various, mostly continuous, optimization problems. For all such heuristically guided search algorithms balance between exploitation and exploration is the determining factor for success. It is generally considered that in the ABC algorithm exploitation is performed by employed ...