An Improved Variable Neighbourhood Search for Solving Work Scheduling and Routing Problem in the Inline Final Inspection Process

In the manufacturing industry, on-time delivery and quality assurance are imperative. An electronic manufacturing company performs inline final inspection processes on each production order at the related production area to guarantee quality. However, this process entails additional travel time to reach the designated location, resulting in delivery delays. This research focuses on route optimization and task scheduling for the quality department in the manufacturing sector. It proposes an improved variable neighbourhood search, leveraging the time control mechanism of the jellyfish search optimizer (JS) and an enhanced 2-opt operator. The resulting model was compared with the variable neighbourhood search, JS, and the grey wolf optimizer (GWO) on the final inspection dataset acquired from the manufacturing company. The model proved to be effective, achieving the best-known solutions in all instances with an acceptable processing time considering the large number of jobs.