Agent-Based Interaction Protocols and Topologies for Manufacturing Task Allocation

Owliya, Mohammad; Saadat, Mozafar; Jules, Guiovanni; Goharian, M.; Anane, Rachid

doi:10.1109/tsmca.2012.2192263

Cited by 25 publications

(12 citation statements)

References 42 publications

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“…The advantage of the threshold-based method in comparison to the market-based approach is that it avoids the effects of a continuous change of bids, which leaves the indirect threshold approach free from communication scalability complexities (Goldingay & Van Mourik, 2013;Shen, 2002). The other component which acts alongside the negotiation mechanism is the interaction protocol, which manages the time and structure of exchanging data between each agent (Jules, Saadat, & Saeidlou, 2015;Owliya, Saadat, Jules, Goharian, & Anane, 2013).…”

Section: Distributed Agents' Interaction Protocolsmentioning

confidence: 99%

Agent-based distributed manufacturing scheduling: an ontological approach

et al. 2019

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The purpose of this paper is the need for self-sequencing operation plans in autonomous agents. These allow resolution of combinatorial optimisation of a global schedule, which consists of the fixed process plan jobs and which requires operations offered by manufacturers. The proposed agent-based approach was adapted from the bio-inspired metaheuristic-particle swarm optimisation (PSO), where agents move towards the schedule with the best global makespan. The research has achieved a novel ontology-based optimisation algorithm to allow agents to schedule operations whilst cutting down on the duration of the computational analysis, as well as improving the performance extensibility amongst others. The novelty of the research is evidenced in the development of a synchronised data sharing system allowing better decision-making resources with intrinsic manufacturing intelligence. The multi-agent platform is built upon the Java Agent Development Environment (JADE) framework. The operation research case studies were used as benchmarks for the evaluation of the proposed model. The presented approach not only showed a practical use case of a decentralised manufacturing system, but also demonstrated near optimal makespans compared to the operational research benchmarks.

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Section: Distributed Agents' Interaction Protocolsmentioning

confidence: 99%

Agent-based distributed manufacturing scheduling: an ontological approach

et al. 2019

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“…Most scheduling systems used in industrial environments currently operate centrally and hierarchically [36], that is, with decisions being made at a single point in the system and being passed down to the remaining stations from top to bottom. Although centralization may allow a reliable overview of the system state [31], the use of a centralized top-down approach for task distribution causes rigidity and limits real-world problem-solving capability [40,41]. Hence, a hierarchical and centralized scheduling is ineffective in highly dynamic environments where unexpected events are more frequent.…”

Section: Multi-agent Systemsmentioning

confidence: 99%

“…These tools enable agent classes with specific attributes, as well as creating a virtual environment where these agents can send and receive information. Attendance to FIPA (Foundation for Intelligent Physical Agents), a reference organization responsible for establishing and developing software standards for agents and systems based on agents, is a relevant indicator for choosing the software to be used [40]. Among the available options, reference [75] cite as examples of software developed according to FIPA standards: FIPA-OS, Java Agent Development Environment (JADE), Manufacturing Agent Simulation Tool, ZEUS, MAST and GrassHopper.…”

Section: Technical Details Of Implementationmentioning

confidence: 99%

Solving the Job-Shop Scheduling Problem in the Industry 4.0 Era

et al. 2018

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Technological developments along with the emergence of Industry 4.0 allow for new approaches to solve industrial problems, such as the Job-shop Scheduling Problem (JSP). In this sense, embedding Multi-Agent Systems (MAS) into Cyber-Physical Systems (CPS) is a highly promising approach to handle complex and dynamic JSPs. This paper proposes a data exchange framework in order to deal with the JSP considering the state-of-the-art technology regarding MAS, CPS and industrial standards. The proposed framework has self-configuring features to deal with disturbances in the production line. This is possible through the development of an intelligent system based on the use of agents and the Internet of Things (IoT) to achieve real-time data exchange and decision making in the job-shop. The performance of the proposed framework is tested in a simulation study based on a real industrial case. The results substantiate gains in flexibility, scalability and efficiency through the data exchange between factory layers. Finally, the paper presents insights regarding industrial applications in the Industry 4.0 era in general and in particular with regard to the framework implementation in the analyzed industrial case.

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“…Later, Owliya et al proposed four agent-based models for task allocation in manufacturing shop floor in which two of them employed the CNP. Besides, the prominent position of the agent-based scheduling within the broad area of scheduling was discussed [29]. Lange et al studied a new approach to modeling well scheduling processes in oil and gas industry using the notion of virtual enterprise with intelligent agents and contract net protocol in multi-agent systems technologies, which efficiently assists in the scheduling of resources across the well life cycle [30].…”

Section: Related Workmentioning

confidence: 99%

ANGEL: Agent-Based Scheduling for Real-Time Tasks in Virtualized Clouds

Zhu

Chen

Yang

et al. 2015

IEEE Trans. Comput.

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The success of cloud computing makes an increasing number of real-time applications such as signal processing and weather forecasting run in the cloud. Meanwhile, scheduling for real-time tasks is playing an essential role for a cloud provider to maintain its quality of service and enhance the system's performance. In this paper, we devise a novel agent-based scheduling mechanism in cloud computing environment to allocate real-time tasks and dynamically provision resources. In contrast to traditional contract net protocols, we employ a bidirectional announcement-bidding mechanism and the collaborative process consists of three phases, i.e., basic matching phase, forward announcement-bidding phase and backward announcement-bidding phase. Moreover, the elasticity is sufficiently considered while scheduling by dynamically adding virtual machines to improve schedulability. Furthermore, we design calculation rules of the bidding values in both forward and backward announcement-bidding phases and two heuristics for selecting contractors. On the basis of the bidirectional announcement-bidding mechanism, we propose an agent-based dynamic scheduling algorithm named ANGEL for real-time, independent and aperiodic tasks in clouds. Extensive experiments are conducted on CloudSim platform by injecting random synthetic workloads and the workloads from the last version of the Google cloud tracelogs to evaluate the performance of our ANGEL. The experimental results indicate that ANGEL can efficiently solve the real-time task scheduling problem in virtualized clouds.

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Agent-Based Interaction Protocols and Topologies for Manufacturing Task Allocation

Cited by 25 publications

References 42 publications

Agent-based distributed manufacturing scheduling: an ontological approach

Agent-based distributed manufacturing scheduling: an ontological approach

Solving the Job-Shop Scheduling Problem in the Industry 4.0 Era

ANGEL: Agent-Based Scheduling for Real-Time Tasks in Virtualized Clouds

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