Determination of optimal chance double sampling plan using genetic algorithm

Article type: Research Article

Authors: Sampath, S.^{a; *} | Deepa, S.P.^b

Affiliations: [a] Department of Statistics, University of Madras, Chennai, Tamil Nadu, India | [b] SDNB Vaishnav College for Women, Chennai, Tamil Nadu, India

Correspondence: [*] Corresponding author: S. Sampath, Department of Statistics, University of Madras, Chennai 600005, Tamil Nadu, India. E-mail: [email protected].

Abstract: This paper is meant for identifying the sample sizes and acceptance numbers required for designing double sampling plan applicable for situations involving randomness as well as impreciseness. A genetic algorithm has been suggested to determine the optimal sample sizes and acceptance numbers for specified producer's risk and consumer's risk. Optimal double sampling plans are obtained numerically by implementing the algorithm for different choices of quantities involving triangular fuzzy membership function.

Keywords: Chance distribution, hybrid binomial distribution, double sampling plan, average sample number, average total inspection and genetic algorithm

DOI: 10.3233/MAS-130264

Journal: Model Assisted Statistics and Applications, vol. 8, no. 4, pp. 265-273, 2013