Stochastic transportation problem with random demand and route choice

Abstract

Importance: this article focuses on cost optimization in cargo delivery processepp. Transportation logistics challenges represent a highly relevant and rapidly evolving area in economics, particularly amid digital transformation and the growth of goods delivery servicepp. Consequently, there is a need for effective modeling of real-world scenarios in this industry. Purpose: to develop and solve a stochastic discrete dynamic transportation model that accounts for demand fluctuations and route selection based on environmental conditions and road congestion. Research design: the study involved designing the model and its solution algorithm, implementing the solution in MS Excel and Python, comparing the advantages and limitations of the two tools for the given problem, and conducting simulation experiments to assess the impact of specific factors on the optimal solution. Results: the proposed model serves as a modification of the stochastic transportation problem and can be extended with additional parameters and constraints depending on specific client requirementpp. The problem can be solved in both MS Excel and Python, with Python offering greater flexibility for large-scale simulations and complex transportation scenariopp. The model has practical applications in various transportation logistics systempp.