Abstract
The accomplishment of a manufacturing company’s objectives is strongly connected to the efficient solution of scheduling problems that are faced in the production environment. Numerous methods for the solution of these problems have been published. However, very few of them have been adopted by manufacturing companies. This chapter suggests that the basic reason behind this imbalance is the inadequate representation of the scheduling process when designing decision support systems. Hence, the algorithms that are designed and included in these systems might not reflect the problems that actually have to be solved. The relevance of algorithmic design can be improved by using a more complete representation of the scheduling process, which would be highly relevant for increasing the adoption rate of new support systems.
The main contribution of the chapter concerns the development of a theoretical framework for the design of scheduling decision support systems. This framework is based on an interdisciplinary approach that integrates insights from cognitive psychology, computer science, and operations management. The use of this framework implies that the design of a decision support system should start with an examination of the human, organizational, and technical characteristics of the scheduling situation that has to be supported. This information can be obtained and analyzed using appropriate methodologies such as hierarchical task analysis, cognitive task analysis and cognitive work analysis as well as other methodologies, such as interviews, observations, context diagrams, and data flow diagrams. The designer of the decision support system can then match the results of the analysis to the guidelines of the theoretical framework and proceed accordingly.
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Riezebos, J., Hoc, JM., Mebarki, N., Dimopoulos, C., van Wezel, W., Pinot, G. (2010). Design of Scheduling Algorithms. In: Fransoo, J., Waefler, T., Wilson, J. (eds) Behavioral Operations in Planning and Scheduling. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13382-4_12
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