Total tardiness minimization in a flow shop with blocking using an iterated greedy algorithm

Abstract

We highlight in this paper the competitive performance of the Iterated Greedy algorithm (IG) for solving the flow shop problem under blocking. A new instance of IG is used to minimize the total tardiness criterion. Basically, due to the NP-hardness of this blocking problem, we employ another variant of the NEH heuristic to form primary solution. Subsequently, we apply recurrently constructive methods to some fixed solution and then we use an acceptance criterion to decide whether the new generated solution substitutes the old one. Indeed, the perturbation of an incumbent solution is done by means of the destruction and construction phases. Despite its simplicity, the IG algorithm under blocking has shown its effectiveness, based on Ronconi and Henriques benchmark, when compared to state-ofthe- art meta-heuristics.