| Title: |
Expert System Models for Forecasting Forklifts Engagement in a Warehouse Loading Operation: A Case Study |
| Authors: |
Mirčetić, Dejan; Ralević, Nebojša; Nikoličić, Svetlana; Maslarić, Marinko; Stojanović, Đurđica |
| Source: |
Promet - Traffic&Transportation ; ISSN 1848-4069 (Online) ; ISSN 0353-5320 (Print) ; ISSN-L 0353-5320 ; CODEN POMEEZ ; Volume 28 ; Issue 4 |
| Publisher Information: |
University of Zagreb Faculty of Traffic and Transport Sciences |
| Publication Year: |
2016 |
| Collection: |
Hrčak - Portal of scientific journals of Croatia / Portal znanstvenih časopisa Republike Hrvatske |
| Subject Terms: |
forklifts; loading operation; expert systems; machine learning; ANFIS; CART tree |
| Description: |
The paper focuses on the problem of forklifts engagement in warehouse loading operations. Two expert system (ES) models are created using several machine learning (ML) models. Models try to mimic expert decisions while determining the forklifts engagement in the loading operation. Different ML models are evaluated and adaptive neuro fuzzy inference system (ANFIS) and classification and regression trees (CART) are chosen as the ones which have shown best results for the research purpose. As a case study, a central warehouse of a beverage company was used. In a beverage distribution chain, the proper engagement of forklifts in a loading operation is crucial for maintaining the defined customer service level. The created ES models represent a new approach for the rationalization of the forklifts usage, particularly for solving the problem of the forklifts engagement incargo loading. They are simple, easy to understand, reliable, and practically applicable tool for deciding on the engagement of the forklifts in a loading operation. |
| Document Type: |
text |
| File Description: |
application/pdf |
| Language: |
English |
| Relation: |
https://hrcak.srce.hr/165540 |
| Availability: |
https://hrcak.srce.hr/165540; https://hrcak.srce.hr/file/244271 |
| Rights: |
info:eu-repo/semantics/openAccess ; This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge. The Faculty of Transport and Traffic Sciences at the University of Zagreb would like to see the journal PROMET – Traffic&Transportation become a place of discussion and contemplation on new ideas by scientists and experts in the field of traffic and transport technology. Therefore we have decided to provide free and open access in order to provide all walks of scientists, researchers and individuals with new ideas a place where they can publish and protect their work. The Journal has ensured open access to older issues (from 1990 to 2001) at the Journal web site (https://trafficandtransportation.fpz.hr). |
| Accession Number: |
edsbas.9AC60B1E |
| Database: |
BASE |