Goal Programming in Quality Function Deployment Using Genetic Algorithm

Quality function deployment (QFD) is a systematic approach that captures customer requirements and translates them, through house of quality (HOQ), into technical characteristics of the product. An important activity in constructing a HOQ is to determine improvement ratios for the technical characteristics, based on the collected customer requirements, with a view to achieving a high level of overall customer satisfaction. Traditional methods for this planning process are mainly subjective, and often result in a non-optimal or sub-optimal solution, especially with many customer requirements and technical characteristics. This paper presents a goal programming approach to QFD planning. We first present a generic goal programming model for QFD. We then propose a genetic algorithm for linear and nonlinear goal programming models in QFD. Computational experiments show that the proposed approach is effective.