In this highly volatile, uncertain, complex, and ambiguous (VUCA) environment, a fuzzy inventory optimization problem is a hot topic that received the most attention from both academicians and practitioners. In this paper, the authors have studied the integrated inventory problems under trade credit in fuzzy environments, where the demand rate and deterioration rate are taken here as triangular fuzzy numbers. Accordingly, three types of fuzzy programming models as fuzzy expected cost minimization model, fuzzy α-cost minimization model, and credibility maximization model are built according to different management goals. Since the problem is shown to be NP-hard, this research focuses on proposing a hybrid intelligent algorithm by integrating fuzzy simulation, neural network, and genetic algorithm for solving these models. Then, some numerical examples are presented to illustrate the benefits of the models and evaluate the efficiency of the algorithms. The computational experiments show that the trade credit strategy has a positive impact on improving the supply chains performance and reducing its total cost. In addition, the maximum relative error of the objective values is less than 1, which implies that the hybrid intelligent algorithm is robust to the parameter settings and effective in solving our models. Finally, the practical implications are discussed and useful managerial insights are given.

The planning and scheduling of production determine the economic benefits of enterprise greatly. In this paper, an integration strategy of multi-period collaborative optimization for production planning and scheduling based on data-driven yield model is proposed. Both expert knowledge and historical production data are used to build the yield model of unit. Considering the purchase plan of raw material, inventory of current raw material, sales price of product and equipment production, the multi-period planning and scheduling collaborative optimization strategy (MPSCOS) is established dynamically. The plan and industry production scheme of raw material processing can quickly be obtained by MPSCOS, which helps gain maximum benefit under the condition of safe production. The application effect of MPSCOS is introduced by a practical case. It shows that the model based on dynamic production process can effectively improve the maintainability; the yield model based on data-driven is more accurate than the traditional yield model, as well as the model updating is convenient; the collaborative model of planning and scheduling can effectively connect the planning with scheduling, and further improve the business efficiency of enterprises.