A multi-attribute, rank-dependent utility model for selecting dispatching rules

The use of dispatching rules is one of the most popular solutions used when handling dynamic scheduling problems. However, how best to select a suitable dispatching rule or rules depends on the stochastic behavior of the performance of the system with respect to multiple conflicting attributes. Previous studies based on multi-objective optimization approaches have not explored the subjective information presented by the decision-maker in relation to the multiple impacts that arise from the decisions made using the dispatching rule. This study takes into consideration a rank-dependent utility approach combined with a multi-attribute utility theory to identify the best dispatching rule for dynamic job shop environments. An additive, non-expected, multi-attribute utility function is modeled to represent the decision-maker's preferences and attitude to risk over the multiple stochastic consequences associated with each simulated heuristic. A numerical simulation with realistic data from a furniture hardware industry is performed to demonstrate the usefulness of the proposed decision approach, and the practical issues that emerge are discussed. (C) 2018 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.