E3S Web Conf.
Volume 258, 2021Ural Environmental Science Forum “Sustainable Development of Industrial Region” (UESF-2021)
|Number of page(s)||7|
|Section||Sustainable Transport and Green Logistics|
|Published online||20 May 2021|
Optimization of perishable goods delivery in supply chains with random demand
1 Peter the Great St. Petersburg Polytechnic University (SPbPU), Graduate School of Business and Management, 29, Polytechnicheskaya, 195251, St. Petersburg, Russia
2 People’s Friendship University of Russia (RUDN University), 6, Miklukho-Maklaya Str., Moscow, Russia
3 Karaganda State Technical University, Karaganda, Russia
* Corresponding author: email@example.com
The article suggests a model for defining a rational range and volume of supply of perishable goods in their supply chains functioning at the time of random demand. In the verbal formulation, the goal of the model is to determine the range and delivery volumes of perishable goods that maximize profits with restrictions on the funds available for their purchase, storage volumes and weight, as well as on lost profits. The formalized representation of the model is determined by the properties of the supplied perishable goods. If these goods are divisible, then the model is formalized as a linear programming problem. In this case, the rational assortment and volume of goods is determined by solving it, for example, using the simplex method.If the goods under consideration are piece (indivisible), they are formalized in the form of a corresponding integer programming problem. In this case, the rational assortment and volume of goods is determined by solving it, for example, based on the branch and bound method. The peculiarity of the model is that it takes into account the stochastic nature of demand for goods, their limited shelf life, as well as the possibility of storing goods and the availability of funds necessary to purchase the next batch.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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