Alexander Tsarev. Multi-agent supply planning methods allowing the real-time performance of the supply network management systems // V. Marik et al. (Eds.): Proceedings of the 9th International Conference on Industrial Applications of Holonic and Multi-Agent Systems (HoloMAS’2019), August 26-28, 2019, Linz, Austria. – HoloMas 2019, LNAI 11710. – P. 81-95, 2019. Springer International Publishing, Switzerland, 2019. DOI:https://link.springer.com/chapter/10.1007%2F978-3-030-27878-6_7.
The paper deals with the questions of how to develop the automated planning systems that are fast enough to be used in real-time management of supply networks, considering the manual plan corrections by the users. Several practical situations and planning system use cases are considered. The paper proposes several methods that allow the increase of the data processing speed in practical cases. The methods include parallel data processing, dynamic control of the solutions space depth search, self-regulation of the system behavior based of the speciﬁcs of the data processed.
Alexander Tsarev, Petr Skobelev, Igor Mayorov. Self-regulation of Agents Using Individual Profit Expectations in Multi-agent Scheduling for Supply Management // Proceedings of the 28th International Conference on Computer Applications in Industry and Engineering (CAINE 2015), October 12-14, 2015, San Diego, California, USA. – P. 197-202.
The paper focuses on the development of methods of self-adaptation of agent societies in multi-agent scheduling systems allowing them to achieve higher scheduling quality in changing environments. The paper introduces a self-regulation method based on the agent expectation of achievable profit and on the level of truthfulness in agent interactions. It is described how the profit expectations and the declaration of these expectations affect the scheduling quality in different cases. The paper shows the importance of coordinated behaviour of agents. The approach to coordinated self-regulation and to proactive schedule improvement is proposed. Finally, the results of real data scheduling using the proposed approach are given.
Alexander Tsarev, Dmitry Ochkov, Petr Skobelev. Effective interaction in asynchronous multi-agent environment for supply scheduling in real-time // Proceedings of the Eleventh International Conference on Autonomic and Autonomous Systems (ICAS 2015), May 24 — 29, 2015 — Rome, Italy. – Xpert Publishing Services, 2015. – P. 120-125.
This paper focuses on analysis of effective interaction techniques of agents in multi-agent systems used for real-time scheduling. The paper describes two approaches to the organization of the interaction of asynchronously working software agents. The supply network scheduling case is considered to show the difference in how the interaction goes on. The comparison shows how well each approach allows parallel processing, and subsequently, how fast the scheduling can be done on multi-core hardware. The pros and cons of the approaches are described, as well as ways to achieve better quality. Finally, the results of processing of real data using the approaches are given. The results show a higher effectiveness of one of the approaches in real-time supply scheduling.
Bjorn Madsen. Design & Deployment of an Enterprise Grade Real-time Multi Agent System for Supply Chain Synchronization // Proceedings of the 12th IEEE/ACIS International Conference on Computer and Information Science 2013 (ICIS 2013), Toki Messe, June 16-20, 2013, Niigata, Japan. – P. 77-82.
To respond to customer demand businesses invest in capacities and supply. Any mismatch results in obsolescent stock, wasted resources and lost sales. In this paper the considerations for design & deployment of an Enterprise Grade Real-time Multi Agent System for supply chain synchronization is presented, so that each and every business involved in the supply chain can adjust their activities to minimize the wasted resources.
Bjorn Madsen, George Rzevski, Petr Skobelev, Alexander Tsarev. A Strategy for Managing Complexity of the Global Market and Prototype Real-time Scheduler for LEGO Supply Chain // International Journal of Software Innovation, 2013. – Vol.1, Issue 2. – P. 28-39. – DOI: 10.4018/ijsi.2013040103.
The paper describes main features of a strategy for managing complexity of the global market and real-time scheduling multi-agent system designed for the LEGO Company. The design is based on Multi-Agent Technology Group (MATech) own strategy blueprint and multi-agent platform, which provide real-time adaptive event-driven scheduling to replenish products to LEGO Branded Retail stores. The prototype system has been used to schedule 20 US-based LEGO retail outlets for a yearlong trial period and has achieved the following results: • Reduction of lost sale from 40% to 16%; • Increase in service level from 66% to 86%; • Increase in profitability 56% to 81%. The results show a considerable potential value for full scale LEGO supply chain multi-agent solution which would be able to dynamically and adaptively re-schedule deliveries in real time.
Bjorn Madsen, George Rzevski, Petr Skobelev, Alexander Tsarev. Real-time Multi-Agent Forecasting & Replenishment Solution for LEGOs Branded Retail Outlets. – Proceedings of the 13th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2012), August 8-10, 2012, Kyoto, Japan. – pp. 451-456.
The paper describes main features of a real-time forecasting and scheduling multi-agent solution designed for the LEGO Company. The design is based on Knowledge Genesis Group own multi-agent platform and technology, which provide real-time adaptive event-driven scheduling to replenish products to LEGO Branded Retail stores. The prototype system has been used to schedule 20 US-based LEGO retail outlets for a yearlong trial period and has achieved the following results:
• Reduction of lost sale from 40% to 16%;
• Increase in service level from 66% to 86%;
• Increase in profitability 56% to 81%.
The results show a considerable potential value for full scale LEGO supply chain multi-agent solution which would be able to dynamically and adaptively re-schedule deliveries in real time.