Кафедра "Інтернет речей"

The problem of supply management in the supplier-to-consumer logistics transport system has been formed and solved. The novelty of the formulation of the problem consists in the integrated accounting of costs in the logistic system, which takes into account at the same time the cost of transporting products from suppliers to consumers, as well as the costs for each of the consumers to store the unsold product and losses due to possible shortages. The resulting optimization problem is no longer a standard linear programming problem. In addition, the work assumes that the solution of the problem should be sought taking into account the fact that the initial data of the problem are not deterministic. The analysis of traditional methods of describing the uncertainty of the source data. It is concluded that, given the rapidly changing conditions for the implementation of the delivery process in a distributed supplier-to-consumer system, it is advisable to move from a theoretical probability representation of the source data to their description in terms of fuzzy mathematics. At the same time, in particular, the fuzzy values of the demand for the delivered product for each consumer are determined by their membership functions. Distribution of supplies in the system is described by solving a mathematical programming problem with a nonlinear objective function and a set of linear constraints of the transport type. In forming the criterion, a technology is used to transform the membership functions of fuzzy parameters of the problem to its theoretical probabilistic counterparts – density distribution of demand values. The task is reduced to finding for each consumer the value of the ordered product, minimizing the average total cost of storing the unrealized product and losses from the deficit. The initial problem is reduced to solving a set of integral equations solved, in general, numerically. It is shown that in particular, important for practice, particular cases, this solution is achieved analytically. The paper states the insufficient adequacy of the traditionally used mathematical models for describing fuzzy parameters of the problem, in particular, the demand. Statistical processing of real data on demand shows that the parameters of the membership functions of the corresponding fuzzy numbers are themselves fuzzy numbers. Acceptable mathematical models of the corresponding fuzzy numbers are formulated in terms of bifuzzy mathematics. The relations describing the membership functions of the bifuzzy numbers are given. A formula is obtained for calculating the total losses to storage and from the deficit, taking into account the bifuzzy of demand. In this case, the initial task is reduced to finding the distribution of supplies, at which the maximum value of the total losses does not exceed the permissible value.

A transportation problem of linear programming with intermediate centers was considered. For cases where throughputs of intermediate centers are not specified, a problem of calculating rational distribution of the total throughput in order to minimize the average value of total transportation costs has been stated. Several options of constructing the method for solving the problem were proposed. The first option implements the iterative procedure of successive improvement of the initial distribution of throughputs of the centers by the Nelder-Mead method. Increase in speed of this method was achieved using the duality theory. The second option is based on a preliminary solution of the problem of finding optimal routes for all pairs "supplier-consumer" taking into account a possible intermediate center. In this case, the usual two-index transportation problem of delivering products from the system of suppliers to the system of consumers arises. The optimal plan of this task contains necessary data to calculate required throughput for each of the intermediate centers. Advantage of this method consists in the possibility of its effective propagation for solving problems with a multilayered structure of intermediate centers.

Кафедра "Інтернет речей"

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