Applying Iterative Flattening Search to the Job Shop Scheduling Problem with Alternative Resources and Sequence Dependent Setup Times

This paper tackles a complex version of the Job Shop Scheduling Problem (JSSP) that involves both the possibility to select alternative resources to activities and the presence of sequence dependent setup times. The proposed solving strategy is a variant of the known Iterative Flattening Search (IFS) metaheuristic. This work presents the following contributions: (1) a new constraint-based solving procedure produced by means of enhancing a previous JSSP-solving version of the same metaheuristic; (2) a new version of both the variable and value ordering heuristics, based on temporal flexibility, that capture the relevant features of the extended scheduling problem (i.e., the flexibility in the assignment of resources to activities, and the sequence dependent setup times); (3) a new relaxation strategy based on the random selection of the activities that are closer to the critical path of the solution, as opposed to the original approach based on a fully random relaxation. The performance of the proposed algorithm are tested on a new benchmark set produced as an extension of an existing well-known testset for the Flexible Job Shop Scheduling Problem by adding sequence dependent setup times to each original testset\u27s instance, and the behavior of the old and new relaxation strategies are compared