Intelligent Agent for Modeling and Processing Decisional Workflows in Logistics

Intelligent Agent for Modeling and Processing Decisional Workflows in Logistics

Thomas Tamisier (Centre de Rercherche Public - Gabriel Lippmann, Luxembourg) and Fernand Feltz (Centre de Rercherche Public - Gabriel Lippmann, Luxembourg)
Copyright: © 2011 |Pages: 9
DOI: 10.4018/jeei.2011100104
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Abstract

The authors present the design and some implementation trials of Atlas, a new reasoning and decision making assistant used for processing complex and heterogeneous procedural workflows. Benefiting from a multicore implementation, Atlas includes different solving engines that are selected according to the intrinsic complexity of the problem being processed. The operational knowledge of Atlas is accessed through 2 different views. In an analytical view, the knowledge is modeled on elementary if-then rules, which are processed by a resolution engine written in the Soar architecture. A synthetic view offers a pictorial representation of all the knowledge, and in particular, shows the inter-dependence of the rules and their procedural references. In addition to allowing an efficient processing, the system checks the coherence of the knowledge and produces a justification of the decision with respect to relevant operational procedures.
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Introduction

Owing to their ability to easily organize and update heterogeneous knowledge, Decision-Support Systems form a promising approach for the optimization of logistics businesses (Gordon, 1994; Fehling, 1993). The management and visualization of the knowledge base of these systems are in this regard crucial to ensure a proper functioning and to keep an intuitive view of their expected behavior (Asproth, 2007). They have in fact taken a significant importance for a large set of daily life and business problems that can be formalized through inference rules and combinational cases (Marakas, 1998; Groothuis & Svensson, 2000). In particular, decision support tools are gaining ground both in large companies and public administrations, especially for the efficient handling of dynamic operational requests, such as the (re-) ascribing of tasks (Allen & Greenleaf, 2001) and in logistics control (Almejalli et al., 2004) or planning (Grosche & Rothlauf, 2004).

A historical crossroad in Eastern Europe, the Grand-Duchy of Luxembourg is nowadays characterized by the interconnection between rail, air and route transportation and an increasingly huge traffic. The project Atlas (Assistance to Transportational Logistics by Automated System) is concerned with the use of Decision-Support Systems to sustain the growth of the country as a prominent logistics place. Atlas seeks to offer tailored solutions for transport management, and dedicated to all economic actors of the supply chain, whether seeking the best way to comply with administrative, legal, and business constraints, or willing to improve on important features such as secure collaboration, traceability, or multimodality. In particular, the decision system will help dealing with the EU-shaped freight framework, notably characterized by the development of multimodality, aids to take off road transport, and new working rules for truck drivers.

As a main result, we develop a collaborative expert system aimed at processing regulation and operational rules related to multimodal freight transportation and involving the European and national contexts. To ease the integration in the working infrastructure of the larger number of related business and administration services, Atlas is deployed as an aggregation of web services supporting collaborating work inside and between organizations. The operators access them, according to specific rights depending on their pre-recorded user profiles, to share and manage their tasks, and to edit or update the knowledge base without the help of a computer specialist. Owing to the flexibility of its reasoning scheme, of its deployment, and of its usability Atlas can therefore be viewed as multi-purpose professional reasoning architecture

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