Due‐Window Assignment and Scheduling with Multiple Rate‐Modifying Activities under the Effects of Deterioration and Learning

Abstract

This paper discusses due‐window assignment and scheduling with multiple rate‐modifying activities. Multiple types of rate‐modifying activities are allowed to perform on a single machine. The learning effect and job deterioration are also integrated concurrently into the problem which makes the problem more realistic. The objective is to find jointly the optimal location to perform multiple rate‐modifying activities, the optimal job sequence, and the optimal location and size of the due window to minimize the total earliness, tardiness, and due‐window‐related costs. We propose polynomial time algorithms for all the cases of the problem under study.