Genetic algorithm for non-linear mixed integer programming problems and its applications
Computers and Industrial Engineering
Journal of Global Optimization
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Music-Inspired Harmony Search Algorithm: Theory and Applications
Music-Inspired Harmony Search Algorithm: Theory and Applications
A novel global harmony search algorithm for reliability problems
Computers and Industrial Engineering
Recent Advances in Optimal Reliability Allocation
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Expert Systems with Applications: An International Journal
Adaptive Memetic Differential Evolution with Global and Local neighborhood-based mutation operators
Information Sciences: an International Journal
Survey A survey on applications of the harmony search algorithm
Engineering Applications of Artificial Intelligence
Hi-index | 12.05 |
Solving reliability-redundancy optimization problems via meta-heuristic algorithms has attracted increasing attention in recent years. In this paper, an effective coevolutionary differential evolution with harmony search algorithm (CDEHS) is proposed to solve the reliability-redundancy optimization problem by dividing the problem into a continuous part and an integer part. In CDEHS, two populations evolve simultaneously and cooperatively, where one population for the continuous part evolves by means of differential evolution while another population for the integer part evolves by means of harmony search. After half of the whole evolving process, the integer part stops evolving and provides the best solution to the other part for further evolving with differential evolution. Simulations results based on three typical problems and comparisons with some existing algorithms show that the proposed CDEHS is effective, efficient and robust for solving the reliability-redundancy optimization problem.