Swarm Intelligence Algorithm with Guided Exploitations: A Case Study with Artificial Bee Colony Algorithm
نویسندگان
چکیده
During any meta-heuristic search, two opposite processes are found in action, namely the explorations and exploitations. Although they might seem to operate in opposite directions, they are actually counterparts, and synergy between them may improve the final outcome of the algorithm. This is especially true for complex, high dimensional problems, because the search algorithm has to avoid many local optima to find a good near optimum solution. There exist many swarm intelligence algorithms that report the necessity of a proper balance between explorations and exploitations. This paper presents a concrete example of a swarm intelligence algorithm, i.e., the Artificial Bee Colony (ABC) algorithm that finds improvement by balancing between explorations and exploitations. In this paper, we have introduced ABC with Guided Exploitations (ABC-GE), a novel algorithm that improves over the basic ABC algorithm. ABC-GE augments each candidate solution with a control parameter that controls the proportion of explorative and exploitative perturbations and thus affects how new trial solutions are produced from the existing ones. This control parameter is automatically adjusted at the individual solution level, separately for each candidate solutionxi, to adjust the proportions of explorations and exploitations around xi.ABC-GE is tested on a number of benchmark problems on continuous optimization and compared with the basic ABC algorithm. Results show that the performance of ABC-GE is overall better than the basic ABC algorithm.
منابع مشابه
Balaning Explorations with Exploitations in the Artificial Bee Colony Algorithm for Numerical Function Optimization
This paper introduces a variant of Artificial Bee Colony algorithm and compares its results with a number of swarm intelligence and population based optimization algorithms. The Artificial Bee Colony (ABC) is an optimization algorithm based on the intelligent food foraging behavior of honey bees. The proposed variant, Artificial Bee Colony Algorithm with Balanced Explorations and Exploitations ...
متن کاملBQIABC: A new Quantum-Inspired Artificial Bee Colony Algorithm for Binary Optimization Problems
Artificial bee colony (ABC) algorithm is a swarm intelligence optimization algorithm inspired by the intelligent behavior of honey bees when searching for food sources. The various versions of the ABC algorithm have been widely used to solve continuous and discrete optimization problems in different fields. In this paper a new binary version of the ABC algorithm inspired by quantum computing, c...
متن کاملOPTIMIZATION OF SKELETAL STRUCTURAL USING ARTIFICIAL BEE COLONY ALGORITHM
Over the past few years, swarm intelligence based optimization techniques such as ant colony optimization and particle swarm optimization have received considerable attention from engineering researchers. These algorithms have been used in the solution of various structural optimization problems where the main goal is to minimize the weight of structures while satisfying all design requirements...
متن کاملAn Improved Gbest Guided Artificial Bee Colony Algorithm for Classification and Prediction Tasks
Artificial Neural Networks (ANN) performance depends on network topology, activation function, behaviors of data, suitable synapse's values and learning algorithms. Researchers used different learning algorithms to train ANN for getting high performance. Artificial Bee Colony (ABC) algorithm is one of the latest successfully Swarm Intelligence based technique for training Multilayer Perceptron ...
متن کاملArtificial Bee Colony (ABC) Algorithm with Crossover and Mutation
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 ...
متن کامل