Nonlinear integer goal programming models for acceptance sampling
type: Item
instance of: scholarly article
title: Nonlinear integer goal programming models for acceptance sampling
zbMATH Open document ID: 0615.90091
DOI: 10.1016/0305-0548(86)90054-7
author: Yanyan Li
published in: Computers \& Operations Research
publication date: 1986-01-01T00:00:00Z
review text: Two lexicographic goal programming models are developed for determining the optimal sample size and acceptance number for acceptance sampling plans in quality control. Both models address the conflicting criteria inherent in such sampling problems, namely the average lot inspection cost and the average outgoing quality. The first model assumes a known constant lot fraction defective, while the second relaxes this assumption and instead assumes knowledge of a prior distribution on the fraction of defectives. A three-phase algorithm is develped which exploits the problem structure in order to find optimal solutions after examining a small percentage of the feasible sampling plans. On a set of 64 test problems the algorithm always found the optimal solution, typically after evaluating only 3-5\% (and never more than 9\%) of the feasible points.
Mathematics Subject Classification ID: 90C90
Mathematics Subject Classification ID: 90B50
Mathematics Subject Classification ID: 62P30
Mathematics Subject Classification ID: 90C10
Mathematics Subject Classification ID: 65K05
zbMATH DE Number: 3997569
zbMATH Keywords: lexicographic goal programming
zbMATH Keywords: optimal sample size
zbMATH Keywords: acceptance sampling plans
zbMATH Keywords: quality control
MaRDI profile type: Publication
full work available at URL: 0305-0548(86)90054-7
OpenAlex ID: W2084124825
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description: scientific article; zbMATH DE number 3997569