minimize Header

Prof. Dr. Benedikt Elser

Centre for Applied Research

Technology Campus Grafenau

Professor

A 011

0991/3615-739

publications

Sortierung:

Zeitschriftenartikel

Benedikt Elser
Michael Scholz

Price Optimization of Perishable Goods Using a Genetic Algorithm

In: International Journal of Revenue Management vol. 1 pg. 1.

(2022)

DOI: 10.1504/IJRM.2022.10044440

Abstract anzeigen

Multi-product profit optimisation problems have been studied under nested logit models of consumer behaviour. Although attractive through to the relaxation of strong assumptions of multinomial logit models, nested logit models as well as multinomial logit models require costly discrete choice experiments in order to collect data for estimating model parameters. We propose a novel formulation of multi-product profit optimisation that is especially useful for perishable goods that are of the same type and different only in their quality level. Our model relies on willingness to pay data that can be elicited directly, derived from market data or measured indirectly in auctions or through transactions. We furthermore present a genetic algorithm for solving the formulated multi-product profit optimisation and show that our proposed genetic algorithm finds nearby optimal solutions within a very short time span.

TC Grafenau
NACHHALTIG
DIGITAL

Zeitschriftenartikel

Florian Wahl
Matthias Breslein
Benedikt Elser

On-demand forklift hailing system for Intralogistics 4.0

In: Procedia Computer Science vol. 200 pg. 878-886.

(2022)

DOI: 10.1016/j.procs.2022.01.285

Abstract anzeigen

The shift to I4.0 is happening. While large companies have a range of solutions to implement that change, small and medium-sized enterprises (SME) fall short on solutions tailored for their specific needs. To support SMEs in their transformation toward I4.0, we propose a lightweight system to hail forklifts in a production facility of a medium-sized enterprise. Existing shop floor workflows are implemented within the system and allow machine operators to hail forklift drivers using an embedded or a web-based client. Forklift drivers receive driving instructions on their smartphones. Shift managers can monitor intralogistic activities on a dashboard. Management can extract relevant production and forklift KPIs from the system. In a two-week evaluation phase, we installed our system in a production facility for injection moulded plastic parts. We equipped 12 machines and two forklifts and registered a total of 690 jobs. We found half of the jobs were picked up in 4:05 min and 80% of all jobs were completed in less than 40:02 min.

TC Grafenau
DIGITAL

Zeitschriftenartikel

Marco Kretschmann
Andreas Fischer
Benedikt Elser

Extracting Keywords from Publication Abstracts for an Automated Researcher Recommendation System

In: Digitale Welt (Proceedings of the First International Symposium on Applied Artificial Intelligence in Conjunction with DIGICON) vol. 4 pg. 20-25.

(2020)

DOI: 10.1007/s42354-019-0227-2

Abstract anzeigen

This paper presents an automated keyword assignment system for scientific abstracts. That system is applied to paper abstracts collected in a local publication database and used to drive a researcher recommendation system. Problems like low data volume and missing keywords are discussed. For remediation, training is performed on an extended data set based on large online publication databases. Additionally a closer look at label imbalance in the dataset is taken. Ten multi-label classification algorithms for assigning keywords from a given catalogue to a scientific abstract are compared. The usage of binary relevance as transformation method with LightGBM as classifier yields the best results. Random oversampling before the training phase additionally increases the F1-Score by around 5-6%.

Angewandte Informatik
Angewandte Wirtschaftswissenschaften
DIGITAL

Vortrag

Benedikt Elser

Die digitale Wagenreihung bei der Deutschen Bahn

In: WI-Symposium

Deggendorf

28.10.2018 (2018)

Angewandte Informatik
TC Grafenau
DIGITAL