OPTIMIZATION OF A BICRITERION ACCEPTANCE SAMPLING MODEL
Abstract
A bicriterion model for acceptance sampling in quality control is developed. Such a model allows explicit consideration of conflicting goals that are not considered in existing acceptance sampling schemes. A quality measure and a cost measure are used as the conflicting criteria. Two optimization procedures for solving the model are explored. Method 1 involves the measurement of a decision maker's utility function and subsequent optimization via an implicit enumeration algorithm. Method 2 employs an interactive procedure. A procedure to measure a decision maker's utility function is developed and explored. The method utilizes mathematical programming to simplify the measurement steps of: (1) assessing conditional utility functions and their risk parameters; (2) assessing importance weights for each criteria, and (3) checking for consistency. Also presented is a laboratory study that compares the interactive process to utility function measurement methods in a quality control setting. Claims that interactive procedures are easier to use and achieve a more satisfactory solution were supported. The claim that interactive procedures provide more insight into the relationships of the criteria was refuted. An interactive procedure under uncertainty is developed and illustrated for the bicriterion case. Efficiency under uncertainty is defined, and conditions that guarantee efficiency are proven. The method iteratively moves toward a better solution. The procedure strives to maximize expected utility.
Degree
Ph.D.
Subject Area
Management
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