Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Multiple Objective Optimization with Vector Evaluated Genetic Algorithms
Proceedings of the 1st International Conference on Genetic Algorithms
Comparison of Multiobjective Evolutionary Algorithms: Empirical Results
Evolutionary Computation
Natural Computing: an international journal
Multiobjective optimization problems with complicated Pareto sets, MOEA/D and NSGA-II
IEEE Transactions on Evolutionary Computation
Integral Particle Swarm Optimization with Dispersed Accelerator Information
Fundamenta Informaticae - Swarm Intelligence
Metaheuristics: From Design to Implementation
Metaheuristics: From Design to Implementation
EvoCOP'07 Proceedings of the 7th European conference on Evolutionary computation in combinatorial optimization
Engineering Optimization: An Introduction with Metaheuristic Applications
Engineering Optimization: An Introduction with Metaheuristic Applications
Nature-Inspired Metaheuristic Algorithms: Second Edition
Nature-Inspired Metaheuristic Algorithms: Second Edition
Review of meta-heuristics and generalised evolutionary walk algorithm
International Journal of Bio-Inspired Computation
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
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
Dynamic multiobjective optimization problems: test cases, approximations, and applications
IEEE Transactions on Evolutionary Computation
MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition
IEEE Transactions on Evolutionary Computation
Two-stage eagle strategy with differential evolution
International Journal of Bio-Inspired Computation
Social emotional optimisation algorithm with emotional model
International Journal of Computational Science and Engineering
International Journal of Bio-Inspired Computation
Clustering based on improved bee colony algorithm
International Journal of Computer Applications in Technology
Metaheuristic algorithms for inverse problems
International Journal of Innovative Computing and Applications
Artificial physics optimisation algorithm guided by diversity
International Journal of Computer Applications in Technology
An improved multi-objective genetic algorithm for fuzzy flexible job-shop scheduling problem
International Journal of Computer Applications in Technology
Bat algorithm: literature review and applications
International Journal of Bio-Inspired Computation
International Journal of Bio-Inspired Computation
A bat-inspired algorithm for structural optimization
Computers and Structures
Generation of neural networks using a genetic algorithm approach
International Journal of Bio-Inspired Computation
Bat inspired algorithm for discrete size optimization of steel frames
Advances in Engineering Software
A wrapper approach for feature selection based on Bat Algorithm and Optimum-Path Forest
Expert Systems with Applications: An International Journal
A modified harmony search method for wind generator design
International Journal of Bio-Inspired Computation
Bio-inspired computation: success and challenges of IJBIC
International Journal of Bio-Inspired Computation
An empirical study of test effort estimation based on bat algorithm
International Journal of Bio-Inspired Computation
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Engineering optimisation is typically multi-objective and multidisciplinary with complex constraints, and the solution of such complex problems requires efficient optimisation algorithms. Recently, Xin-She Yang proposed a bat-inspired algorithm for solving non-linear, global optimisation problems. In this paper, we extend this algorithm to solve multi-objective optimisation problems. The proposed multi-objective bat algorithm (MOBA) is first validated against a subset of test functions, and then applied to solve multi-objective design problems such as welded beam design. Simulation results suggest that the proposed algorithm works efficiently.