Title: Assisted discovery of optimal solution for logistics problems using ontology modelling

Authors: Adeel Ahmad; Mourad Bouneffa; Hayder I. Hendi; Cyril Fonlupt

Addresses: Laboratoire d'Informatique Signal et Image de la Côte d'Opale (LISIC), University Littoral Côte d'Opale, UR 4491, F-62100 Calais, France ' Laboratoire d'Informatique Signal et Image de la Côte d'Opale (LISIC), University Littoral Côte d'Opale, UR 4491, F-62100 Calais, France ' College of Computer Science and Math, University of Thi-Qar, Iraq ' Laboratoire d'Informatique Signal et Image de la Côte d'Opale (LISIC), University Littoral Côte d'Opale, UR 4491, F-62100 Calais, France

Abstract: The logistics processes conjointly execute various physical and logical tasks. The physical tasks may concern the elements such as goods to be transported, vehicles, and human resources. Whereas, the logical tasks are generally accomplished by software units that can be fully automatic or interactive such as optimisation methods or event management, etc. The logistics problems are often complex np-hard combinatorial optimisation problems. In this paper, we define the shared conceptual vocabulary concerning the logistics problems and inherent optimisation solutions. The result of the work is a knowledge base system, which is formalised and implemented as a set of ontologies. These have been used as key components of a tool that may assist the logistics expert to identify the related optimisation methods to solve the concerned problem and eventually list the available corresponding web-services implementing them.

Keywords: optimisation ontology; transportation optimisation; automated transportation; optimisation methods; decision support systems; logistics ontology; vehicle routing problems; VRPs.

DOI: 10.1504/IJLSM.2023.128559

International Journal of Logistics Systems and Management, 2023 Vol.44 No.1, pp.85 - 104

Received: 19 Nov 2019
Accepted: 09 Jan 2021
Published online: 26 Jan 2023 *