Improved genetic algorithm for minimizing periodic preventive maintenance costs in series-parallel systems

  • Authors:

  • Chung-Ho Wang;Te-Wei Lin

  • Affiliations:

  • Department of Power Vehicle and Systems Engineering, Chung Cheng Institute of Technology, National Defense University, Taoyuan, Taiwan R.O.C.;Department of Power Vehicle and Systems Engineering, Chung Cheng Institute of Technology, National Defense University, Taoyuan, Taiwan R.O.C.

  • Venue:
  • ICA3PP'10 Proceedings of the 10th international conference on Algorithms and Architectures for Parallel Processing - Volume Part I
  • Year:
  • 2010

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Abstract

This work presents an improved genetic algorithm (IGA) for minimizing periodic preventive maintenance costs in series-parallel systems The intrinsic properties of a repairable system, including the structure of reliability block diagrams and component maintenance priorities are considered by the proposed IGA The proposed component importance measure considers these properties, identifies key components, and determines their maintenance priorities The optimal maintenance periods of these important components are then determined to minimize total maintenance cost given the allowable worst reliability of a repairable system An adjustment mechanism is established to solve the problem of chromosomes falling into infeasible areas A response surface methodology is further used to systematically determine crossover probability and mutation probability in the GA instead of using the conventional trial-and-error process A case study demonstrates the effectiveness and practicality of the proposed IGA for optimizing the periodic preventive maintenance model in series-parallel systems.