A hybrid Jaya algorithm for reliability–redundancy allocation problems. Issue 4 (3rd April 2018)

• Record Type: Journal Article
• Authors: Ghavidel, Sahand; Azizivahed, Ali; Li, Li
• Is Part Of: Engineering optimization. Volume 50:Issue 4(2018)
• Page Start: 698
• Page End: 715
• Publication Date: 2018-04-03
• Subjects: Jaya algorithm -- reliability–redundancy allocation problems (RRAPs) -- teaching–learning-based optimization (TLBO) algorithm -- time-varying acceleration coefficients; Engineering design -- Periodicals; Mathematical optimization -- Periodicals; 620.0042
• DOI: 10.1080/0305215X.2017.1337755
• Languages: English
• ISSNs: 0305-215X

Abstract

ABSTRACT: This article proposes an efficient improved hybrid Jaya algorithm based on time-varying acceleration coefficients (TVACs) and the learning phase introduced in teaching–learning-based optimization (TLBO), named the LJaya-TVAC algorithm, for solving various types of nonlinear mixed-integer reliability–redundancy allocation problems (RRAPs) and standard real-parameter test functions. RRAPs include series, series–parallel, complex (bridge) and overspeed protection systems. The search power of the proposed LJaya-TVAC algorithm for finding the optimal solutions is first tested on the standard real-parameter unimodal and multi-modal functions with dimensions of 30–100, and then tested on various types of nonlinear mixed-integer RRAPs. The results are compared with the original Jaya algorithm and the best results reported in the recent literature. The optimal results obtained with the proposed LJaya-TVAC algorithm provide evidence for its better and acceptable optimization performance compared to the original Jaya algorithm and other reported optimal results.