Open AccessResearch of Multi-objective Component Assignment Problem for Lin/con/k/n System Considering Cost
Author(s) -
Mamunur Rashid,
Huiying Cao,
Chenyang Ma,
Mudassar Rehman,
Zhiqiang Cai
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1043/3/032070
Subject(s) - component (thermodynamics) , heuristics , reliability (semiconductor) , sorting , mathematical optimization , computer science , reliability engineering , genetic algorithm , scheme (mathematics) , algorithm , mathematics , engineering , mathematical analysis , power (physics) , physics , quantum mechanics , thermodynamics
Component assignment problem (CAP) is widely used in engineering systems, which is investigated for enhancing the system performance by assigning switchable components to several positions. However, the traditional CAP does not consider the cost factor and has limitations for improving the system reliability. Therefore, this paper focus on a multi-objective CAP for Lin/con/k/n system to find the cost-efficient maintenance scheme. Firstly, a multi-objective mathematical optimization model is developed with the aim of maximizing the system reliability and minimizing maintenance cost, which has been proved to be a Non-deterministic polynomial hard problem and should be computed by heuristics. Secondly, a comprehensive maintenance method is adopted to improve the system reliability, which integrates improving the system reliability with changing the permutation of components. To evaluate the contribution of the component reliability on both system reliability and maintenance cost, the multi-objective Birnbaum importance (MOBI) is derived. Finally, MOBI is introduced into the non-dominated sorting genetic algorithm-II (NSGA-II) to solve the optimization model. The numerical experiments for several Lin/con/k/n Systems show that MOBI is available to solve CAP considering cost, and MOBI-based-NSGA-II algorithm is more efficient to obtain higher system reliability with lower maintenance cost.