Bi-objective sequence optimization in reliability problems with a matrix-analytic approach

被引:0
|
作者
Mohammad N. Juybari
Pardis Pourkarim Guilani
Mostafa Abouei Ardakan
机构
[1] Kharazmi University,Department of Industrial Engineering, Faculty of Engineering
来源
关键词
Mixed strategy; Redundancy allocation problem; Bi-objective model; Markov chain; Sequence optimization;
D O I
暂无
中图分类号
学科分类号
摘要
The redundancy allocation problem (RAP) is an intriguing area in the field of reliability optimization to which a lot of research has been devoted in recent years. In this paper, a bi-objective model is developed for RAP with a heterogeneous backup scheme and a mixed redundancy strategy. Elimination of the lower bound estimation and the exact calculation of the reliability of the mixed strategy forms one of the most striking features of the proposed model. Investigating the optimal sequence of components in each subsystem, the study modifies a non-dominated sorting genetic algorithm (NSGA-II), as a powerful multi-objective evolutionary one, to solve the proposed bi-objective model. Two numerical examples will then be used to verify the efficiency of the model in achieving enhanced system reliability. Finally, the results of Pareto optimal set are used to demonstrate that the assumptions made enable the proposed model to improve system reliability by offering various structures while simultaneously considering system limitations.
引用
收藏
页码:275 / 304
页数:29
相关论文
共 50 条
  • [41] A bi-objective optimization approach to reducing uncertainty in pipeline erosion predictions
    Dai, Wei
    Cremaschi, Selen
    Subramani, Hariprasad J.
    Gao, Haijing
    [J]. COMPUTERS & CHEMICAL ENGINEERING, 2019, 127 : 175 - 185
  • [42] A Parameterless-Niching-Assisted Bi-objective Approach to Multimodal Optimization
    Bandaru, Sunith
    Deb, Kalyanmoy
    [J]. 2013 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2013, : 95 - 102
  • [43] A Bi-Objective Approach for Product Recommendations
    Benouaret, Idir
    Amer-Yahia, Sihem
    Kamdem-Kengne, Christiane
    Chagraoui, Jalil
    [J]. 2019 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2019, : 2159 - 2168
  • [44] Column generation algorithms for bi-objective combinatorial optimization problems with a min-max objective
    Artigues, Christian
    Jozefowiez, Nicolas
    Sarpong, Boadu M.
    [J]. EURO JOURNAL ON COMPUTATIONAL OPTIMIZATION, 2018, 6 (02) : 117 - 142
  • [45] Bi-objective Bayesian optimization of engineering problems with cheap and expensive cost functions
    Nasrulloh Loka
    Ivo Couckuyt
    Federico Garbuglia
    Domenico Spina
    Inneke Van Nieuwenhuyse
    Tom Dhaene
    [J]. Engineering with Computers, 2023, 39 : 1923 - 1933
  • [46] Mixed-Integer Benchmark Problems for Single- and Bi-Objective Optimization
    Tusar, Tea
    Brockhoff, Dimo
    Hansen, Nikolaus
    [J]. PROCEEDINGS OF THE 2019 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE (GECCO'19), 2019, : 718 - 726
  • [47] Bi-Objective Median Subtree Location Problems
    J.W. George
    C.S. ReVelle
    [J]. Annals of Operations Research, 2003, 122 : 219 - 232
  • [48] Bi-objective Bayesian optimization of engineering problems with cheap and expensive cost functions
    Loka, Nasrulloh
    Couckuyt, Ivo
    Garbuglia, Federico
    Spina, Domenico
    Van Nieuwenhuyse, Inneke
    Dhaene, Tom
    [J]. ENGINEERING WITH COMPUTERS, 2023, 39 (03) : 1923 - 1933
  • [49] Bi-Objective Colored Traveling Salesman Problems
    Xu, Xiangping
    Li, Jun
    Zhou, MengChu
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 23 (07) : 6326 - 6336
  • [50] Bi-objective median subtree location problems
    George, JW
    Revelle, CS
    [J]. ANNALS OF OPERATIONS RESEARCH, 2003, 122 (1-4) : 219 - 232