In this paper, we study a flow shop batch processing machines scheduling problem. The fuzzy due dates are considered to make the problem more close to the reality. The objective function is taken as the weighted sum of fuzzy earliness and fuzzy tardiness. In order to tackle the given problem, we propose a hybrid electromagnetism-like (EM) algorithm, in which the EM is hybridized with a diversification mechanism and effective local search to enhance the efficiency of the algorithm. The proposed algorithms are evaluated by comparison against two existing well-known EMs in the literature. Additionally, we propose some heuristics based on the earliest due date (EDD) to solve the given problem. The proposed hybrid EM algorithm is tested on sets of various randomly generated instances. For this purpose, we investigate the impacts of the rise in problem sizes on the performance of the developed algorithm. Through the analysis of the experimental results, the highly effective performance of the proposed algorithm is shown against the two existing well-known EMs from the literature and proposed EDDs.