An Evolutionary Algorithm For the Vehicle Routing Problem with Drones with Interceptions

Autor: Pambo, Carlos, Grobler, Jacomine

The use of trucks and drones as a solution to address last-mile delivery challenges is a new and promising research direction explored in this paper. The variation of the problem where the drone can intercept the truck while in movement or at the cus

Externí odkaz: http://arxiv.org/abs/2409.14173

Cyber-security: Identity deception detection on social media platforms

Autor: van der Walt, Estee, Eloff, J.H.P., Grobler, Jacomine

Publikováno v: In Computers & Security September 2018 78:76-89

Particle swarm optimization and differential evolution for multi-objective multiple machine scheduling

Autor: Grobler, Jacomine

Production scheduling is one of the most important issues in the planning and operation of manufacturing systems. Customers increasingly expect to receive the right product at the right price at the right time. Various problems experienced in manufac

Externí odkaz: http://hdl.handle.net/2263/25790
http://upetd.up.ac.za/thesis/available/etd-06242009-105320/

Improving stock target setting (STS) parameters used in the automotive supply chain: A case study.

Autor: Botha, Andries¹, Grobler, Jacomine¹ jacomine.grobler@up.ac.za, Yadavalli, Sarma¹

Publikováno v: Management Dynamics / Bestuursdinamika. 2017, Vol. 26 Issue 4, p20-34. 15p.

Robotic flow shop scheduling with parallel machines and no-wait constraints in an aluminium anodising plant with the CMAES algorithm

Autor: Behr, Carina M., Grobler, Jacomine, Rutkowski, Leszek, Scherer, Rafal, Korytowski, Marcin, Pedrycz, Witold, Tadeusiewicz, Ryszard, Zurada, Jacek M.

Publikováno v: Artificial Intelligence and Soft Computing-17th International Conference, ICAISC 2018, Proceedings, 302-312
STARTPAGE=302;ENDPAGE=312;TITLE=Artificial Intelligence and Soft Computing-17th International Conference, ICAISC 2018, Proceedings
Artificial Intelligence and Soft Computing ISBN: 9783319912523
ICAISC (1)

This paper proposes a covariance matrix adaptation evolution strategy (CMAES) based algorithm for a robotic flow shop scheduling problem with multiple robots and parallel machines. The algorithm is compared to three popular scheduling rules as well a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6c3f849cb452a6fbb835e7ccba94e394
https://research.utwente.nl/en/publications/77b96ae9-f533-4fd4-96e1-0158f7632658