Novel Heuristic Algorithm & its Application for Reliability Optimization

Author:

Dahiya Tripti1,Vashishth Nakul2,Garg Deepika2,Shrivastava Avinash K.3,Kapur P. K.4

Affiliation:

1. Department of Mathematics, G.D. Goenka University, Gurgaon, India.

2. Department of Mathematics, G.D. Goenka University, Gurgaon, India.

3. Department of Operations Management and Quantitative Techniques, International Management Institute, Kolkata, West Bengal, India.

4. Amity Center for Interdisciplinary Research, Amity University, Noida, Uttar Pradesh, India.

Abstract

Heuristic algorithms are practical, easy to implement, and work fast to provide short-term, feasible solutions for any kind of problem within economical budgets as compared to other meta-heuristic algorithms. This paper presents a novel heuristic algorithm named the Dahiya-Garg Heuristic Algorithm (DG-Alg) to find the optimal solution for constrained reliability redundancy allocation optimization problems. The cornerstone of the novel DG-Alg is its novel selection factor, which is a mathematical formula that helps the heuristic algorithm search for optimal subsystems for reliability optimization. A novel formulated selection factor in DG-Alg has increased its effectiveness and efficiency. To analyze the performance of the proposed heuristic algorithm and the other three existing heuristic algorithms, they are applied to a problem taken from a pharmaceutical manufacturing plant named Yaris Pharmaceuticals. During the application of the heuristic algorithms, it was ensured that redundancy allocation was done within stipulated cost constraints. Further, a comparative analysis of the obtained results has been done to judge the performance of the proposed heuristic algorithm. It is deduced that the proposed heuristic algorithm gives optimized and computationally efficient results in comparison to the other existing heuristic algorithms.

Publisher

Ram Arti Publishers

Subject

General Engineering,General Business, Management and Accounting,General Mathematics,General Computer Science

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