Penalty guided genetic search for reliability design optimization
Computers and Industrial Engineering
Genetic algorithm for non-linear mixed integer programming problems and its applications
Computers and Industrial Engineering
A linear approximation for redundant reliability problems with multiple component choices
Computers and Industrial Engineering
A knowledge management system for series-parallel availability optimization and design
Expert Systems with Applications: An International Journal
A cross entropy based algorithm for reliability problems
Journal of Heuristics
Expert Systems with Applications: An International Journal
Reliability analysis of waste clean-up manipulator using genetic algorithms and fuzzy methodology
Computers and Operations Research
Expert Systems with Applications: An International Journal
Reliability analysis of complex multi-robotic system using GA and fuzzy methodology
Applied Soft Computing
A PSO algorithm for constrained redundancy allocation in multi-state systems with bridge topology
Computers and Industrial Engineering
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This paper presents a novel algorithm for solving a series-parallel redundancy allocation problem with separable constraints. The idea of a heuristic approach design is inspired from the greedy method and the genetic algorithm. The structure of the algorithm includes: (1) randomly generating a specified population size number of minimum workable solutions; (2) assigning components either according to the greedy method or to the random selection method; and (3) improving solutions through an inner-system and intersystem solution revision process. Numerical results for the 33 test problems from previous research are reported and compared. As reported in this paper, the solutions found by our approach are all better than or are in par with the well-known best solutions from the approach taken by previous solutions.