Data-Driven Robust Optimization for Solving the Heterogeneous Vehicle Routing Problem with Customer Demand Uncertainty

Table 1

Parameters and symbols.

Parameter	Implication
Q^k	The standard capacity of the kth vehicle
cij	The length of the edge (i, j) ∈ E (the travel distance between node i to node j)
ε	Represents the penalty factor ε
	Represents the amount of unmet customer needs
yik	This is a 0-1 variable. When the value is 1, it means that customers i is delivered by vehicle k; if the value is 0, it means other cases
xijk	This is a 0-1 variable. When the value is 1, it means that the vehicle k moves from node i to j; if the value is 0, it indicates other conditions
	This is a 0-1 variable. When the value is 1, it means that  > 0; if the value is 0, it means other cases
fk	Fixed cost of vehicle type k