A method for performance analysis of a genetic algorithm applied to the problem of fuel consumption minimization for heavy-duty vehicles
Artikel i vetenskaplig tidskrift, 2019

This paper presents a general method for assessment of the performance of a genetic algorithm (GA)in cases where the global optimum of the objective function is unknown. The method involves discretization of the search space, making it possible to apply a brute force calculation to find the global optimum for the discretized case. Then, this method is used to study the performance of a GA applied to the problem of speed profile optimization for heavy-duty vehicles, in which the optimization must be carried out within a rather short time. In this performance analysis, the discretization involves generating speed profiles as piecewise linear functions. It is demonstrated that the GA is able to find near-optimal solutions for the cases considered here: The speed profiles generated by the GA have objective function values that are typically within 2% of the global optimum.

Genetic algorithms

Fuel-efficient driving

Speed profile optimization


Sina Torabi

Chalmers, Mekanik och maritima vetenskaper, Fordonsteknik och autonoma system

Mattias Wahde

Chalmers, Mekanik och maritima vetenskaper, Fordonsteknik och autonoma system

Applied Soft Computing Journal

1568-4946 (ISSN)

Vol. 80 735-741




Matematisk analys



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