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Abstract

This research presents a mathematical model to find the optimal route sequence for vehicle routing problems with uncertain travel speeds. The objective is to solve the problem of organizing routes for vehicles with uncertain travel speeds by determining the most suitable route sequence to minimize the total travel time under various constraints, including the chance-constrained model. The chance-constrained model represents the probability distribution of travel speeds for each route, assumed to follow a normal distribution. Mathematical equations of this problem, formulated with the chance-constrained model, were then transformed into a form that can be solved using the LINGO program. The results of routing obtained from the LINGO program reduced the time spent on operations from 516 minutes per week to 337.38 minutes per week. Additionally, it decreased the transportation distance from 233.34 kilometers per week to 186.36 kilometers per week and saved fuel costs of 604.8 Baht per month, resulting in a cost reduction of 9.08%. In summary, constructing a mathematical model with a chance-constrained model related to the uncertainty of travel speeds and utilizing the LINGO program to solve the problem can indeed reduce transportation time and costs effectively. This led to a reduction in operational costs and ensured faster delivery to customers in the case study of a drinking water factory.