# Application Of Cacs Approach For Distributed Logistic Systems

## Sami Al-Maqtari1, Habib Abdulrab1, Eduard Babkin1 2

Abstract. The article offers original approach which is called Controller Agent for Constraints Satisfaction (CACS). That approach combines multi-agent architecture with constraint solvers in the unified framework which expresses major features of Swarm Intelligence approach and replaces traditional stochastic adaptation of the swarm of the autonomous agents by constraint-driven adaptation. We describe major theoretic, methodological and software engineering principles of composition of constraints and agents in the framework of one multi-agent system, as well as application of our approach for modelling of particular logistic problem. 12

## 1. Introduction

Simultaneous rapid grow of logistics market in different regions of the world [1, 2], and its important role in modern economy require wide application of logistics information and management systems for coordinated planning and control. Distributed organizational structure and application of holonic management principles in modern organizations inevitably determine distributed and autonomous features of information systems supporting logistic operations [5]. In such kinds of the systems it is very difficult to apply usual centralized approaches and algorithms for decision support and optimization.

Swarm Intelligence [3, 4] represents one of the interesting paradigm for maintaining self-organization and control in the distributed systems. One of the principal aspect of the swarmoriented distributed intelligent systems is presence of multiple intellectual and autonomous particles which interact with each other in some way. As it is started in [4]: ‖Swarm is a population of interacting elements that is able to optimize some global objectives thought collaborative search in space‖. 

Different projects offered approaches for practical application of Swarm Intelligence paradigm in the form of multi-agent systems [6, 28, 30]. Although some of them (i.e. [28]) offer a formal framework for declarative expression and analysis, researchers and practitioners still lack proper generic methods for engineering of the multi-agent systems which have such properties of Swarm Intelligence as emergent behavior, peer-topeer communication, etc.

Analysis of known logistic problems and algorithms shows that in the domain of applied logistics and optimization general principles of swarm-oriented organization may be realized using proper combination of multi-agent systems (MAS) and constraints satisfaction approach (CSP). So, in this research we 
 
1LITIS Laboratory, INSA Rouen, France. Email: {**almaqtari**, 
abdulrab}**@insa-rouen.fr**.

2TAPRADESS Laboraotry, State University - Higher School of Economics, Nizhny Novgorod, Russia. Email: **eababkin@hse.ru**.

pursue the goal to offer a new mechanism of emergent multiagent behaviour for collaborative search of some feasible solution in accordance with certain inter-agent constraints. In terms of Swarm Intelligence research we replace stochastic adaptation of the swarm of the autonomous agents by constraintdriven adaptation.

In our research we try to satisfy such important requirements of Swarm Intelligence as self-organization and dynamic adaptation to evolving internal or external conditions. Existing approaches to combination of MAS and CSP like [16, 17, 32] do not provide much flexibility and support of dynamic modification of the combined structure of agents and constraints. That's why in this article we propose an original approach which offers a solution for dynamic modification of the combined structure of agents and constraints. Our approach, which was called CACS (Controller Agent for Constraints Satisfaction), allows for joint exploitation of attractive features of the paradigm of multi-agent systems (MAS) and the paradigm of distributed constraint satisfaction (DCSP).

This paper extends and combines our earlier work on joint application of MAS and DCSP paradigms [33, 34]. We describe major theoretic, methodological and software engineering principles of composition of constraints and agents in the framework of one multi-agent system, as well as application of our approach for modelling of particular logistic problem. 

The paper is organized as follows. In Section 2 we give background information about MAS and DCSP for better understanding of scientific and technological foundations of our research. In Section 3 we describe main principles of CACS approach. Section 4 contains description of software architecture and implementation principles for software prototype which supports proposed CACS approach. The same section contains overview of used 3d party software platforms. Section 5 describes proposed methodology of practical application of CACS during design and development of DSS. In Section 6 we give overview of the application in ship loading logistics based on CACS prototype. We discuss the achieved results and provide directions for future work in Section 7.

## 2. Foundations Of Mas And Dcsp

Paradigm of swarm intelligence is very often and naturally implemented on the basis of multi-agent systems. These systems express major features of collective intelligence [7, 8, 9] and represent the model of problem in terms of autonomous entities that live in a common environment and who share certain resources. The interactions between these individual entities induce cognitive abilities of the whole. Despite multiple-domainoriented peculiarities majority of multi-agent systems has several significant common features: 