Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Swarm intelligence
On the performance of artificial bee colony (ABC) algorithm
Applied Soft Computing
Artificial Bee Colony (ABC) Optimization Algorithm for Solving Constrained Optimization Problems
IFSA '07 Proceedings of the 12th international Fuzzy Systems Association world congress on Foundations of Fuzzy Logic and Soft Computing
A heuristic particle swarm optimization method for truss structures with discrete variables
Computers and Structures
A survey: algorithms simulating bee swarm intelligence
Artificial Intelligence Review
Engineering optimizations via nature-inspired virtual bee algorithms
IWINAC'05 Proceedings of the First international work-conference on the Interplay Between Natural and Artificial Computation conference on Artificial Intelligence and Knowledge Engineering Applications: a bioinspired approach - Volume Part II
Structural and Multidisciplinary Optimization
Identification of structural models using a modified Artificial Bee Colony algorithm
Computers and Structures
Sizing truss structures using teaching-learning-based optimization
Computers and Structures
A new hybrid artificial bee colony algorithm for robust optimal design and manufacturing
Applied Soft Computing
A survey of non-gradient optimization methods in structural engineering
Advances in Engineering Software
A new optimization method: Dolphin echolocation
Advances in Engineering Software
Fully Stressed Design Evolution Strategy for Shape and Size Optimization of Truss Structures
Computers and Structures
Artificial bee colony algorithm: a survey
International Journal of Advanced Intelligence Paradigms
Structural and Multidisciplinary Optimization
Krill herd algorithm for optimum design of truss structures
International Journal of Bio-Inspired Computation
Computers & Mathematics with Applications
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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 and practitioners. These algorithms have been used in the solution of various engineering problems. Recently, a relatively new swarm based optimization algorithm called the Artificial Bee Colony (ABC) algorithm has begun to attract interest from researchers to solve optimization problems. The aim of this study is to present an optimization algorithm based on the ABC algorithm for the discrete optimum design of truss structures. The ABC algorithm is a meta-heuristic optimization technique that mimics the process of food foraging of honeybees. Originally the ABC algorithm was developed for continuous function optimization problems. This paper describes the modifications made to the ABC algorithm in order to solve discrete optimization problems and to improve the algorithm's performance. In order to demonstrate the effectiveness of the modified algorithm, four structural problems with up to 582 truss members and 29 design variables were solved and the results were compared with those obtained using other well-known meta-heuristic search techniques. The results demonstrate that the ABC algorithm is very effective and robust for the discrete optimization designs of truss structural problems.