A multiobjective-optimization approach for a piloted quality-management system: A comparison of two approaches for a case study

In recent years, steering a quality-management system (QMS) has become a key strategic consideration in businesses. Indeed, companies constantly need to optimize their industrial tools to increase their productivity and to permanently improve the effectiveness and efficiency of their systems. To solve such problems, two approaches were developed: the Pareto Analytical-Hierarchy Process (PAHP) and the Multichoice Goal Programming (MCGP) methods. The first integrates the Pareto concept and Analytical-Hierarchy Process (AHP) methods and the second combines the MCGP model with AHP methods. The goal was to determine the best solution while simultaneously verifying multiobjective-optimization functions and satisfying different constraints for a real-world case study. The latter was chosen because it presents a major problem for controlling the quality levels of production lines. A comparative study between the two approaches provides a path for designing a tool for decision support to ensure the effectiveness of a corporate QMS.