Modelling a Warehouse with SLICER: A Contribution to the MULTI Warehouse Challenge

In this paper we apply the SLICER multi-level modelling framework on the MULTI 2024 Warehouse Challenge. SLICER was first introduced at the ER 2015 conference[17] and formally specified in [18]. It has been implemented in an object-oriented knowledge representation and reasoning system and the framework identifies additional semantic subcategories for the traditional object-oriented relationship types and uses these distinctions for a new style of formal characterisation of level relationships. The framework is executable via its implementation in a dynamic metamodeling and object logic environment. We first introduce SLICER, then describe its application on the Warehouse Challenge requirements and then discuss the advantages of the SLICER representation.

Authors

Institutions

Publication Details

Published
2024-09-22
DOI
https://doi.org/10.1145/3652620.3688215
Primary Topic
Advanced Manufacturing and Logistics Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Modelling a Warehouse with SLICER: A Contribution to the MULTI Warehouse Challenge

Markus Stumptner, Matt Selway, Georg Großmann, Karamjit Kaur et al.
Advanced Manufacturing and Logistics Optimization
article

Modelling a Warehouse with SLICER: A Contribution to the MULTI Warehouse Challenge

Markus Stumptner, Matt Selway, Georg Großmann, Karamjit Kaur, Yuhong Fu
article en

Abstract

In this paper we apply the SLICER multi-level modelling framework on the MULTI 2024 Warehouse Challenge. SLICER was first introduced at the ER 2015 conference[17] and formally specified in [18]. It has been implemented in an object-oriented knowledge representation and reasoning system and the framework identifies additional semantic subcategories for the traditional object-oriented relationship types and uses these distinctions for a new style of formal characterisation of level relationships. The framework is executable via its implementation in a dynamic metamodeling and object logic environment. We first introduce SLICER, then describe its application on the Warehouse Challenge requirements and then discuss the advantages of the SLICER representation.

University of South Australia (AU)
Decent work and economic growth
Openalex Percentile: Top 72%
Advanced Manufacturing and Logistics Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.