论文标题
简化的群体优化，用于双反射主动可靠性冗余分配问题
Simplified Swarm Optimization for Bi-Objection Active Reliability Redundancy Allocation Problems
论文作者
论文摘要
可靠性冗余分配问题（RRAP）是系统设计，开发和管理中的著名工具。 RRAP始终被建模为非线性混合企业非确定性多项式硬度（NP-HARD）问题。为了最大化系统的可靠性，必须确定整数（组件主动冗余级别）和实际变量（组件可靠性），以确保满足成本限制和某些非线性约束。在这项研究中，通过更改成本限制作为新目标来提出双向目标RRAP，因为有必要平衡整个系统在实际应用中的可靠性和成本影响。为了解决提出的问题，具有惩罚功能的新的简化群体优化（SSO），一种真正的单年溶液结构，一种基于数字的自适应新的更新机制，受约束的非主导解决方案选择以及新的Pbest替换策略是根据这些结构从全面设计中选择的，以找到帕累托式的可置换和有效地有效地开发这些结构。拟议的SSO的表现优于几种元疗法的最先进算法，例如，根据涉及Bi-Ixptive Activies Active Rrap的四个基准测试结果，根据实验结果，非自愿的分类遗传算法II（NSGA-II）和多目标粒子群优化（MOPSO）。
The reliability redundancy allocation problem (RRAP) is a well-known tool in system design, development, and management. The RRAP is always modeled as a nonlinear mixed-integer non-deterministic polynomial-time hardness (NP-hard) problem. To maximize the system reliability, the integer (component active redundancy level) and real variables (component reliability) must be determined to ensure that the cost limit and some nonlinear constraints are satisfied. In this study, a bi-objective RRAP is formulated by changing the cost constraint as a new goal, because it is necessary to balance the reliability and cost impact for the entire system in practical applications. To solve the proposed problem, a new simplified swarm optimization (SSO) with a penalty function, a real one-type solution structure, a number-based self-adaptive new update mechanism, a constrained nondominated-solution selection, and a new pBest replacement policy is developed in terms of these structures selected from full-factorial design to find the Pareto solutions efficiently and effectively. The proposed SSO outperforms several metaheuristic state-of-the-art algorithms, e.g., nondominated sorting genetic algorithm II (NSGA-II) and multi-objective particle swarm optimization (MOPSO), according to experimental results for four benchmark problems involving the bi-objective active RRAP.
