Iterative PSO Algorithms for GRAP Problems

Fang LU, Dong-kui LI

Abstract


This paper studies the grap problems of two-state, in which the subsystem allows components to be mixed (i.e. the subsystem selects components from several types of heterogeneous components, and the number of selected components types >=1). Each component has a fixed reliability, weight and price, and determines the number of selected components, so that the system has the greatest reliability under the given cost and weight constraints. The coding method of the solution is that the number of elements of each type of subsystem is a variable, and the whole system is arranged in the order of subsystems to form row vectors. An iterative particle swarm optimization algorithm with fixed compression coefficient and dynamic inertia weight is constructed to solve the problem. Typical improved fyffe problems are tested, and the optimal solutions are obtained, which are consistent with the results given by the substitution constraint method. The pso algorithm presented in this paper can effectively solve the grap problem which is allowed to mix components in subsystems.

Keywords


Mixed components, The reliability redundancy allocation problem, Particle swarm optimization algorithm, Encoding, Optimal solution


DOI
10.12783/dtcse/aicae2019/31454

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