Structural optimization based on second-order approximations of functions and dual theory
Computer Methods in Applied Mechanics and Engineering
Genetic algorithms with sharing for multimodal function optimization
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Punctuated equilibria: a parallel genetic algorithm
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Parallel genetic algorithms for a hypercube
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Intelligence through simulated evolution: forty years of evolutionary programming
Intelligence through simulated evolution: forty years of evolutionary programming
Immune network modelling in design optimization
New ideas in optimization
Use of a self-adaptive penalty approach for engineering optimization problems
Computers in Industry
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Migration Policies, Selection Pressure, and Parallel Evolutionary Algorithms
Journal of Heuristics
Improving flexibility and efficiency by adding parallelism to genetic algorithms
Statistics and Computing
Distributed Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Structure and Performance of Fine-Grain Parallelism in Genetic Search
Proceedings of the 5th International Conference on Genetic Algorithms
A Segregated Genetic Algorithm for Constrained Structural Optimization
Proceedings of the 6th International Conference on Genetic Algorithms
Proceedings of the 11 IPPS/SPDP'99 Workshops Held in Conjunction with the 13th International Parallel Processing Symposium and 10th Symposium on Parallel and Distributed Processing
Selected Papers from AISB Workshop on Evolutionary Computing
Gado: a genetic algorithm for continuous design optimization
Gado: a genetic algorithm for continuous design optimization
Advances in Engineering Software - Special issue on evolutionary optimization of engineering problems
How Do We Evaluate Artificial Immune Systems?
Evolutionary Computation
An Adaptive Multimeme Algorithm for Designing HIV Multidrug Therapies
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
An improved genetic algorithm with initial population strategy and self-adaptive member grouping
Computers and Structures
Future Generation Computer Systems
Adaptive cellular memetic algorithms
Evolutionary Computation
Structure assembling by stochastic topology optimization
Computers and Structures
Meta-Lamarckian learning in memetic algorithms
IEEE Transactions on Evolutionary Computation
A tutorial for competent memetic algorithms: model, taxonomy, and design issues
IEEE Transactions on Evolutionary Computation
A Fast Adaptive Memetic Algorithm for Online and Offline Control Design of PMSM Drives
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Coevolving Memetic Algorithms: A Review and Progress Report
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Weight minimization of trusses with genetic algorithm
Applied Soft Computing
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A new genetic algorithm (GA) methodology, Bipopulation-Based Genetic Algorithm with Enhanced Interval Search (BGAwEIS), is introduced and used to optimize the design of truss structures with various complexities. The results of BGAwEIS are compared with those obtained by the sequential genetic algorithm (SGA) utilizing a single population, a multipopulation-based genetic algorithm (MPGA) proposed for this study and other existing approaches presented in literature. This study has two goals: outlining BGAwEIS's fundamentals and evaluating the performances of BGAwEIS and MPGA. Consequently, it is demonstrated that MPGA shows a better performance than SGA taking advantage of multiple populations, but BGAwEIS explores promising solution regions more efficiently than MPGA by exploiting the feasible solutions. The performance of BGAwEIS is confirmed by better quality degree of its optimal designations compared to algorithms proposed here and described in literature.