Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Penalty guided genetic search for reliability design optimization
Computers and Industrial Engineering
Artificial Immune Systems: A New Computational Intelligence Paradigm
Artificial Immune Systems: A New Computational Intelligence Paradigm
A linear approximation for redundant reliability problems with multiple component choices
Computers and Industrial Engineering
On the computational complexity of reliability redundancy allocation in a series system
Operations Research Letters
An artificial immune algorithm for the flexible job-shop scheduling problem
Future Generation Computer Systems
Penalty guided PSO for reliability design problems
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Solving reliability redundancy allocation problems using an artificial bee colony algorithm
Computers and Operations Research
Expert Systems with Applications: An International Journal
Redundant space manipulator optimization design based on genetic algorithm of immunity
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
Application of immune algorithms on solving minimum-cost problem of water distribution network
Mathematical and Computer Modelling: An International Journal
Journal of Intelligent Manufacturing
Multi-objective reliability-redundancy allocation problem using particle swarm optimization
Computers and Industrial Engineering
Optimal sequencing of warm standby elements
Computers and Industrial Engineering
A PSO algorithm for constrained redundancy allocation in multi-state systems with bridge topology
Computers and Industrial Engineering
Hi-index | 0.00 |
This paper considers the series-parallel redundant reliability problems in which both the multiple component choices of each subsystem and the redundancy levels of every selected component are to be decided simultaneously so as to maximize the system reliability. The reliability design optimization problem has been studied in the literature for decades, usually using mathematical programming or heuristic optimization approaches. The difficulties encountered for both methodologies are the number of constraints and the difficulty of satisfying the constraints. A penalty-guided immune algorithms-based approach is presented for solving such integer nonlinear redundant reliability design problem. The results obtained by using immune algorithms-based approach are compared with the results obtained from 33 test problems from the literature that dominate the previously mentioned solution techniques. As reported, solutions obtained by the proposed method are better than or as well as the previously best-known solutions.