Процедуры решения транспортных задач в среде MS Excel
This is the first book that presents basic ideas of optimization methods that are applicable to strategic planning and operations management, particularly in the field of transportation. The material of the book covers almost all parts of optimization and is a unique reference work in the field of operations research. The author has written an invaluable manual for students who study optimization methods and their applications in strategic planning and operations management. He describes the ideas behind the methods (with which the study of the methods usually starts) and substantially facilitates further study of the methods using original scientific articles rather than just textbooks. The book is also designed to be a manual for those specialists who work in the field of management and who recognize optimization as the powerful tool for numerical analysis of the potential and of the competitiveness of enterprises. A special chapter contains the basic mathematical notation and concepts useful for understanding the book and covers all the necessary mathematical information.
On the one hand, the relevance of this research is determined by an attempt of solving the problem of optimal inventory allocation, which can open the possibilities for increase in stock turnover. On the other hand, there was an attempt to extend the list of problems which can be solved by operations research methods. The potential of application of operations research methods (transport model as a specific case of linear programming, in particular) is underestimated. According to Taha , a transport model is a problem of finding optimal allocation of homogeneous objects from accumulators (a i ) to receivers (b i ) with minimizations of costs on displacement or movement. In our opinion, the canonical form of a transport model represents accumulators as points of departures, receivers as clients and cost on displacement as transport costs. The paradigm of using this model is constrained by using the latter in transport logistics only. In fact we can apply this model in much more problems (micro, meso or macro level). This study shows that objects and variables from the canonical transport model can be represented as objects from different fields (beyond logistics) thus helping to find an optimal solution to a certain problem. Our study represents accumulators as nominal cells where work-in-process (WIP) product is in the warehouse, receivers - as production lines and costs on displacements as mileage of loaders. Thus, the cost function Z that we want to optimize is the function of mileage of loaders. Minimizing function Z will enable us to find the optimal allocation of WIP products to production lines (next production stage)