Selection of dispatching rules with fuzzy ANP approach

Nowadays, the requirement of flexibility in manufacturing has been increased rapidly because of severe market competition in which customer demand should be met in a right time and in a right way. Although there can be many reasons which affect productivity of the flexible manufacturing system (FMS), one of the crucial one is a scheduling policy which depends upon dispatching rules selection. Selection of a best dispatching rule can only be based on one or two criteria such as processing time, due date, or manufacturing system information in traditional methods such as mathematical programming, simulation, and heuristic algorithms. In addition, traditional methods have some weakness such as the following: first one is that dispatching rules do not allow the use of multiple criteria for evaluating process, second one is related with not considering most of the manufacturing system information, and the last one deals with selection decision not being a dynamic structure. In this study, an analytical network process model based on benefit, opportunity, cost, and risk has been developed in order to eradicate these weaknesses. The model is based on a multiple-criteria decision-making process which contains different performance criteria, details of FMS information, a company's strategic criteria, and different well-known dispatching rules. In addition, that fuzziness of information was also considered in the evaluation process.