<p>Hubs are of great importance in the design of transportation networks because of their use of economies of scale. However, in a competitive business environment, customer preferences should not be neglected. This article assumes a hub network with soft delivery time windows for the transmitted goods between each origin-destination pair. The proposed bi-objective mixed integer mathematical model provides a detailed delivery schedule for the customers. While the first objective function minimizes total transportation costs, the second objective function maximizes customer satisfaction with delivery time. The proposed model belongs to the class of NP-hard problems. Therefore, a soft computing–based framework has been developed to solve it efficiently. In the proposed framework, a modified NSGA-II is combined with a fuzzy group decision-making method to help decision makers select the appropriate solution from a set of compromise solutions. Additionally, the proposed framework involves the qualitative factors as well as the quantitative factors in the decision-making process. Besides the novel chromosome structure for the problem, a dynamic immigration operator is introduced to improve the performance of the proposed NSGA-II. The parameter tuning is done using Taguchi <i>L</i>₉ design of experiments. The comparison of several evaluation metrics in numerical experiments confirms the effectiveness of the proposed improvements on the algorithm performance.</p>