MAGAZINE №1(84) February 2018

AUTHOR Kuznetsov V.O.  - Postgraduate student, Department of Logistics and Supply Chain Management, National Research University Higher School of Economics (St.-Petersburg, Russia)



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 [2011], a transport model is a problem of finding optimal allocation of homogeneous objects from accumulators  to receivers  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)

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