Comparison of Nawaz-Enscore-Ham Algorithm and Local Search Operator in Flowshop Scheduling with Learning Effects

Attention to scheduling problems with learning effect has increased, since the factors that influence productivity of manual tasks are being considered recently. The flowshop system is one of the most frequent configurations of hand-intensive production systems; it belongs to the class of NP-hard combinatorial optimization problems. Thus, this article develops an algorithm to resolve the flowshop scheduling problem with learning effect with makespan minimization. Four models for calculating the learning effect referred to in the literature are considered (according to the position and the sum of the processing times). This paper proposes the Nawaz-Enscore-Ham Algorithm (NEH) with two local search operators. This algorithm is tested through computer experiments.