A framework for single machine multiple objective sequencing research

The majority of single machine sequencing research has assumed that only one objective is to be minimized. The research involving multiple objectives has been limited. Recent studies have shown, however, that production managers often consider multiple objectives when making scheduling decisions. The primary reason for the lack of literature on multiple objective scheduling is the additional complexity encountered when determining the 'best' solution. Although a host of general multiple objective optimization procedures exists, the vast majority cannot be efficiently applied to the multiple objective single machine sequencing problem. Most procedures assume continuous decision variables, whereas the single machine sequencing problem requires integer variables. While some of these procedures could be altered to directly address integer models, the overall combinatorial nature of most sequencing problems limits the applicability to sequencing. A comprehensive review of the published literature on the multiple objective single machine sequencing problem is presented in this paper. A framework is presented to categorize each piece of research. Gaps in the body of research are indicated and recommendations are made for areas of future research.