In classical scheduling models, it is normally assumed that the processing times of jobs are fixed. However, in the recent years, there has been a growing interest in models with variable processing times. Some of the common rationales provided for considering such models, is as follows: the machine conditions may deteriorate as more jobs are processed, resulting in higher than normal processing times, or conversely, the machine’s operator may gain more experience as more jobs are processed, so he/she can process the jobs faster. Another direction of improving the practical relevance of models is by introducing certain rate-modifying activities, such as maintenance periods, in the schedule.
In this thesis, we mainly focus on the study of integrated models which allow changing processing times and rate-modifying activities. When this project was started, it was felt that there was a major scope of improvement in the area, both in terms of creating more general, practically relevant models and developing faster algorithms that are capable of handling a wide variety of problems. In this thesis, we address both these issues.
We introduce several enhanced, practically relevant models for scheduling problems with changing times that allow various types of rate-modifying activities, various effects or a combination of effects on the processing times. To handle these generalised models, we developed a unified framework of algorithms that use similar general principles, through which, the effects of rate-modifying activities can be systematically studied for many different scenarios
