A comparative study of different genetic algorithms approaches to capacitated vehicle routing problem for collection of agricultural products

Platform — Local Producer Marketplace, Publications, UC3 — Local Producer Marketplace

A comparative study of different genetic algorithms approaches to capacitated vehicle routing problem for collection of agricultural products

A comparative study of different genetic algorithms approaches to capacitated vehicle routing problem for collection of agricultural products
Cosmin Sabo, Natanael Balogh, Petrică C. Pop, Adrian Petrovan

Abstract. In this study, we tackle a local collection challenge, employing VRP to address the problem of collecting fresh agricultural products from administrative territorial units. This paper proposes a comparative description of two solution approaches: a haploid genetic algorithm (HGA) and a pseudo-diploid genetic algorithm (P-DGA). We compare the achieved results by the considered genetic algorithms (GAs) on a set of benchmark instances existing from the literature, analyze their performance against state-of-the-art algorithms, and validate them on a second set of instances provided by the Maramureș County Directorate for Agriculture, that contains information regarding the production of tomatoes, onions, and garlic from the administrative units within Maramureș County.

Keywords: capacitated vehicle routing problem; haploid genetic algorithm; diploid genetic algorithm; agricultural products; Maramureș

📋 Cite this publication



Cosmin Sabo, Natanael Balogh, Petrică C. Pop, Adrian Petrovan, "A comparative study of different genetic algorithms approaches to capacitated vehicle routing problem for collection of agricultural products", Proc. 19th SOCO Int. Conf. on Soft Computing Models in Industrial and Environmental Applications, Springer, 2025, pp. 127–136, 2023. DOI: https://doi.org/10.1007/978-3-031-75010-6_13.


Reference: Proc. 19th SOCO Int. Conf. on Soft Computing Models in Industrial and Environmental Applications, Springer, 2025, pp. 127–136. DOI: 10.1007/978-3-031-75010-6_13

Other publications

0 Comments