An environmental logistics firm investigated the efficiency of two different routing algorithms for its fleet of electric delivery vans. The firm measured the energy consumption (in Wh/km) over 50 test journeys for each algorithm:

Algorithm X: Dynamic Eco-routing (prioritising terrain flatness and constant speeds).
Algorithm Y: Shortest-path routing (prioritising absolute distance minimisation).

The results are summarised in Table 1 below.

Table 1: Mean energy consumption and standard deviations for the two routing algorithms

	Algorithm X (Dynamic Eco-routing)	Algorithm Y (Shortest-path routing)
Mean energy consumption (Wh/km)	165.4	198.2
Standard deviation (Wh/km)	12.8	42.5

Algorithm X: Dynamic Eco-routing (prioritising terrain flatness and constant speeds).
Algorithm Y: Shortest-path routing (prioritising absolute distance minimisation).

The results are summarised in Table 1 below.

Table 1: Mean energy consumption and standard deviations for the two routing algorithms

	Algorithm X (Dynamic Eco-routing)	Algorithm Y (Shortest-path routing)
Mean energy consumption (Wh/km)	165.4	198.2
Standard deviation (Wh/km)	12.8	42.5

Data handling and analysis

Question 72

Table 1: Mean energy consumption and standard deviations for the two routing algorithms

Markscheme

Data handling and analysis

Question 72

Table 1: Mean energy consumption and standard deviations for the two routing algorithms

Markscheme

Data handling and analysis

Question 72

Table 1: Mean energy consumption and standard deviations for the two routing algorithms

Data handling and analysis Questions

Data handling and analysis

Question 72

Table 1: Mean energy consumption and standard deviations for the two routing algorithms

Data handling and analysis Questions