Hybrid Optimization Algorithm of Particle Swarm Optimization and Cuckoo Search for Preventive Maintenance Period Optimization

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Abstract
All equipment must be maintained during its lifetime to ensure normal operation. Maintenance is one of the critical roles in the success of manufacturing enterprises. This paper proposed a preventive maintenance period optimization model (PMPOM) to find an optimal preventive maintenance period. By making use of the advantages of particle swarm optimization (PSO) and cuckoo search (CS) algorithm, a hybrid optimization algorithm of PSO and CS is proposed to solve the PMPOM problem. The test functions show that the proposed algorithm exhibits more outstanding performance than particle swarm optimization and cuckoo search. Experiment results show that the proposed algorithm has advantages of strong optimization ability and fast convergence speed to solve the PMPOM problem.
Funding Information
  • National Natural Science Foundation of China (71201026, 2015A030310274, 2015A030310415, 2015A030310315, 2014106101007, 2013108101011)
  • Natural Science Foundation of Guangdong (71201026, 2015A030310274, 2015A030310415, 2015A030310315, 2014106101007, 2013108101011)
  • Natural Science Foundation of Guangdong (71201026, 2015A030310274, 2015A030310415, 2015A030310315, 2014106101007, 2013108101011)
  • Natural Science Foundation of Guangdong (71201026, 2015A030310274, 2015A030310415, 2015A030310315, 2014106101007, 2013108101011)
  • Dongguan Universities and Scientific Research Institutions Science and Technology (71201026, 2015A030310274, 2015A030310415, 2015A030310315, 2014106101007, 2013108101011)
  • Dongguan Social Science and Technology (71201026, 2015A030310274, 2015A030310415, 2015A030310315, 2014106101007, 2013108101011)

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