Nurse rostering is a complex scheduling problem that affects hospital personnel on a daily basis all over the world. The need for quality software solutions is acute for a number of reasons. In particular, it is very important to efficiently utilise time and effort, to evenly balance the workload among people and to attempt to satisfy personnel preferences. A high quality roster can lead to a more contented and thus more effective workforce.In this review, we discuss nurse rostering within the global personnel scheduling problem in healthcare. We begin by briefly discussing the review and overview papers that have appeared in the literature and by noting the role that nurse rostering plays within the wider context of longer term hospital personnel planning. The main body of the paper describes and critically evaluates solution approaches which span the interdisciplinary spectrum from operations research techniques to artificial intelligence methods. We conclude by drawing on the strengths and weaknesses of the literature to outline the key issues that need addressing in future nurse rostering research.
The application of IT and Lean principles have long been seen as mutually exclusive, but both approaches are more and more claimed to be interdependent and complimentary. Real-time production information is crucial to make important business decisions. A Manufacturing Execution System (MES) can provide the necessary support during the Lean journey. MES can trigger, feed or validate the Lean decision making process by providing useful information. In addition, MES can maintain the process improvements by enforcing the standardized way of working. However, this is only possible when MES is aligned and is kept aligned to the Lean objectives. The MES processes must be included in the continuous improvement cycle to prevent them of becoming obsolete. In this work a method is proposed to analyze this alignment between Lean and MES. The Manufacturing Operations Management (MOM) framework provided by ISA 95 is believed to deliver the necessary components to identify and structure this alignment. Mapping MES and Lean activities onto the same framework brings valuable insights about their dependency. The analysis is explored through a case example. Preventing the system of becoming obsolete, by proposing standard model changes, is an important direction for further research.
This paper proposes a new paradigm for tactical demand chain planning (DCP), called robust planning, based on risk assessment of the supply and demand chain. The concepts of supply chain management (SCM), and its extension demand chain management (DCM), have been at the center of much recent research. One of the reasons for this is that, over the last years, a significant number of information systems have emerged, which claim to support the concept. The paper argues that these systems mostly adopt a myopic view of planning, based on pure deterministic planning methods. It demonstrates that such an approach fails to coop with the considerable uncertainty of the planning information. The proposed robust planning paradigm is then introduced and its impact explained, using the well-known example of the beer game. It holds the promise of reducing the number of re-planning cycles, through a better characterization of the expected service level performance over a medium planning horizon. Finally, a case study will show the value of robust planning in a European chemical enterprise.
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