A Strategy for Managing Complexity of the Global Market and Prototype Real-Time Scheduler for LEGO Supply Chain

2013 ◽  
Vol 1 (2) ◽  
pp. 28-39 ◽  
Author(s):  
Bjorn Madsen ◽  
George Rzevski ◽  
Petr Skobelev ◽  
Alexander Tsarev
Keyword(s):  
Supply Chain ◽  
Real Time ◽  
Service Level ◽  
Global Market ◽  
Prototype System ◽  
Agent Platform ◽  
Real Time Scheduling ◽  
Time Scheduling ◽  
Multi Agent ◽  
Managing Complexity

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.

Multithreading MAS Platform for Real-Time Scheduling

2016 ◽  
Vol 4 (1) ◽  
pp. 48-60 ◽  
Author(s):  
Yaroslav Shepilov ◽  
Daria Pavlova ◽  
Daria Kazanskaia
Keyword(s):  
Real Time ◽  
Scheduling Problem ◽  
Optimal Resource Allocation ◽  
Dynamic Changes ◽  
Real Time Scheduling ◽  
Fast Solution ◽  
Agent Scheduling ◽  
Time Scheduling ◽  
Optimal Resource ◽  
Multi Agent

The scheduling is the process of the optimal resource allocation that is widely used both in everyday life and specific domains. In the paper the description of scheduling problem is given. The authors consider traditional methods and tools for solving this problem, then describe the proposed approach based on multi-agent technologies and multithreading application. Nowadays there exist numerous approaches to solving of the scheduling problem. In the most of cases this process has to be supported and managed by the complex tools, sometimes based on mathematical principles. The suggested method of multithreading multi-agent scheduling allows efficient and fast solution of complex problems in real-time featuring rapid dynamic changes and uncertainty that cannot be handled by the other methods and tools.

scholarly journals Real-Time Decision Making in First Mile and Last Mile Logistics: How Smart Scheduling Affects Energy Efficiency of Hyperconnected Supply Chain Solutions

Energies ◽  
2018 ◽  
Vol 11 (7) ◽  
pp. 1833 ◽  
Author(s):  
Tamás Bányai
Keyword(s):  
Energy Efficiency ◽  
Supply Chain ◽  
Energy Consumption ◽  
Real Time ◽  
Real Time Scheduling ◽  
Improve Energy Efficiency ◽  
Increase Energy Efficiency ◽  
Last Mile ◽  
Time Scheduling ◽  
Last Mile Delivery

Energy efficiency and environmental issues have been largely neglected in logistics. In a traditional supply chain, the objective of improving energy efficiency is targeted at the level of single parts of the value making chain. Industry 4.0 technologies make it possible to build hyperconnected logistic solutions, where the objective of decreasing energy consumption and economic footprint is targeted at the global level. The problems of energy efficiency are especially relevant in first mile and last mile delivery logistics, where deliveries are composed of individual orders and each order must be picked up and delivered at different locations. Within the frame of this paper, the author describes a real-time scheduling optimization model focusing on energy efficiency of the operation. After a systematic literature review, this paper introduces a mathematical model of last mile delivery problems including scheduling and assignment problems. The objective of the model is to determine the optimal assignment and scheduling for each order so as to minimize energy consumption, which allows to improve energy efficiency. Next, a black hole optimization-based heuristic is described, whose performance is validated with different benchmark functions. The scenario analysis validates the model and evaluates its performance to increase energy efficiency in last mile logistics.

scholarly journals AI-based methods to resolve Real time scheduling for embedded systems

2021 ◽  
Vol 15 (4) ◽  
pp. 0-0
Keyword(s):  
Embedded Systems ◽  
Real Time ◽  
Artificial Immune Systems ◽  
Multi Agent Systems ◽  
Future Directions ◽  
Real Time Scheduling ◽  
Energy Consumption Reduction ◽  
Consumption Reduction ◽  
Time Scheduling ◽  
Multi Agent

Artificial Intelligence is becoming more attractive to resolve nontrivial problems including the well known real time scheduling (RTS) problem for Embedded Systems (ES). The latter is considered as a hard multi-objective optimization problem because it must optimize at the same time three key conflictual objectives that are tasks deadlines guarantee, energy consumption reduction and reliability enhancement. In this paper, we firstly present the necessary background to well understand the problematic of RTS in the context of ES, then we present our enriched taxonomies for real time, energy and faults tolerance aware scheduling algorithms for ES. After that, we survey the most pertinent existing works of literature targeting the application of AI methods to resolve the RTS problem for ES notably Constraint Programming, Game theory, Machine learning, Fuzzy logic, Artificial Immune Systems, Cellular Automata, Evolutionary algorithms, Multi-agent Systems and Swarm Intelligence. We end this survey by a discussion putting the light on the main challenges and the future directions.

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