No abstract

In this paper a model for the formation of sustainable supply chains of raw materials for a timber processing complex is proposed. The model allows one to optimize the plan of purchases from the Russian Commodity Exchange, as well as the plan of manufacturing finished products. The model presents the task of mathematical programming, whereby the company’s profit is used as the objective function, and the input data include the forecasted values of structure and volumes of offers available on the Russian Commodity Exchange, as well as demand for finished products. The recurrence dependencies of the model describe the flow of raw materials at the enterprise’s warehouse, taking into account revenues from purchased lots, transportation time and consumption of resources that are required for production of simulated volumes of products. Constraints of the model represent formalization of the limited flow of financial resources, taking into account sales and warehouse characteristics. The optimization task deals with variables including volumes of daily output of finished products according to a given nomenclature, as well as variables that specify the inclusion of lots into the portfolio of applications purchased on the exchange. The model solution is found using the branch and bound method with preliminary clipping based on the modified Chvatal–Gomory method. One example considers formation of optimal plans for the purchase and sales in a timber processing complex located in the Primorsky Territory (Russia), which does not have its own forest plots providing production with raw materials. The usefulness of the interaction of the enterprise with the timber department of the commodity and raw materials exchange is assessed.

The relevance of the study of mobile learning as an upcoming trend in education in the context of the COVID-19 pandemic is not denied. The study of students’ ability and motivation to use modern technologies of mobile learning is characterized by novelty. However, the problematic issue of studying the motivation of students and teachers for mobile learning in today's pandemic remains relevant. The purpose of the study is to examine some aspects of the formation of students' motivation (intrinsic motivation: interest in the subject of study, understanding of its significance for further career; extrinsic motivation: points, awards, recognition), as well as the role of teachers in this process and the influence of cognitive abilities of a person on their motivation and academic achievement. The study is based on the method of experiment as well as the interviews and analysis of student reports. There were 185 students (19-22 years old) from Sechenov First Moscow State Medical University and Far Eastern Federal University participating in the study. After the participants had listened to an online lecture on the topic "Neuro-linguistic programming", they were asked to make a report on the topic of the same name and expand the information. Next, the students were interviewed. The results showed that 89% of students were interested in the issue and 69% noted a desire to learn more information on this topic; 100% of participants actively use mobile devices with Internet access for educational purposes and, in particular, for making the required report. However, only 12% of respondents believe that mobile learning alone can be used in order to study specialized disciplines at their university. Thus, 43% of students find it difficult to perceive information from the screen of a smartphone (tablet); 61% of students prefer traditional education to mobile learning, which is probably due to the novelty of this process; 65% of respondents noticed that their knowledge is deteriorating due to the use of mobile (distance) learning. In connection with the results obtained, the following recommendations were made to improve the educational process: to explain to students the importance and usefulness of the topic under study; to use adequate pedagogical methods in the context of mobile learning; to provide feedback and the ability to communicate to students during mobile learning; to take into account the personality and learning style of a student; to use all types of intrinsic and extrinsic motivation of students in accordance with specific circumstances. The most popular motivation factors for mobile learning are possibility of improving exam grades (65%), possibility of improving knowledge (25%), and broadening horizons and deep interest in the topic (10%). Developing applications that will take into account the needs of a particular university and specialty will also make a contribution. Teachers are also encouraged to use a play-based approach and a student reward system in order to increase the level of motivation (additional points, a simplified exam scheme, etc.). The practical significance and prospects for further research are presented by the opportunities of increasing students’ motivation in the context of mobile learning, and, consequently, the success of their studies. The results can be used in the comparative study of mobile learning possibilities in modern conditions and teachers’ involvement in it in different countries.

Supply chain management is a burning issue for modern industrial enterprises. To handle this issue, non-linear stochastic models are successfully applied to find the reasonable and efficient solutions. A need to develop a unique method to find the solutions to supply chain management tasks defined as stochastic mixed-integer non-linear programming tasks is determined by the limitations imposed by the general models. The sum of the total raw procurement costs from the Commodity Exchange over the defined planning horizon is taken to be the target function of the unique model, while the binary variables which show whether a purchasing order is included into the procurement plan are used for optimization purposes. Some parameters of model’s limitations are stochastic and consider the uncertainty factor and risks in supplying the required raw materials to the manufacturing site. Branch-and-bound and genetic algorithms are applied at some steps in the developed heuristic algorithm. The algorithm and the model are tested at a major timber processing enterprise in Primorsky Area. Four types of processors over three planning horizons were applied to compare the efficiency of the proposed algorithm with partial application of the genetic algorithm or branch-and-bound method. The findings analysis shows that, unlike the genetic algorithm, the unique one is more stable in terms of uncertainty of the input parameters in comparison with the branch-and-bound method. It provides the solutions in the models with a great number of variables. The algorithm is shown to be universal enough for its further modification in solving more complicated problems of the same class, containing a significantly larger number of probabilistic parameters that describe other uncertainties in the supply of raw materials. Further research is seen to include the development of the proposed algorithm to increase the rate of convergence for its better efficiency.