Multi-Agent-Based Production Scheduling for Job Shop Manufacturing Systems

2017 ◽  
pp. 143-195
Keyword(s):  
Production Scheduling ◽  
Manufacturing Systems ◽  
Job Shop ◽  
Agent Based ◽  
Multi Agent

scholarly journals Ant Colony Intelligence in Flexible Manufacturing Scheduling Using Contract-Net Model

2011 ◽  
Vol 2-3 ◽  
pp. 608-613
Author(s):  
Ying Zi Wei ◽  
Yi Jun Feng ◽  
Kan Feng Gu
Keyword(s):  
Flexible Manufacturing ◽  
Manufacturing Systems ◽  
Ant Colony ◽  
Contract Net Protocol ◽  
Agent Based ◽  
Contract Net ◽  
Multi Agent ◽  
Bidding Mechanism ◽  
Alternative Processes ◽  
Alternative Machines

This paper builds an efficient agent-based flexible scheduling for real-world manufacturing systems. Considering the alternative processes and alternative machines, the allocation of manufacturing resources is achieved through negotiation among the job and machine agents in a multi-agent system (MAS). Ant Colony Intelligence (ACI) is proposed to be combined with Contract Net Protocol (CNP) so as to make agents adaptive to changing circumstances. ACI is integrated into both machine agents and job agents to solve the task allocation and sequencing problem. CNP is introduced to allow the agents to cooperate and coordinate their local schedules in order to find globally near-optimal robust schedules. The negotiation protocol is an interactive bidding mechanism based on the hybrid contract net protocol. The implementation of the issues using CNP model is discussed. Experimental results verify the effectiveness and efficiency of the proposed algorithm integrated with ant-inspired coordination.

An Optimization Model for Manufacturing Systems in an Uncertain Environment

2015 ◽  
Author(s):  
Michael Mitnovitsky ◽  
Miri Weiss Cohen ◽  
Moshe Shpitalni
Keyword(s):  
Manufacturing Systems ◽  
Job Shop ◽  
Adaptive Control System ◽  
Operational Flexibility ◽  
Agent Based ◽  
Machine Breakdowns ◽  
Processing Times ◽  
Dynamic Events ◽  
Increase Productivity ◽  
Flexible Job Shop Problem

This paper examines a flexible job shop problem that considers dynamic events, such as stochastic job arrivals, uncertain processing times, unexpected machine breakdowns and the possibility of processing flexibility. To achieve this goal, a new agent-based adaptive control system has been developed at the factory level, along with advanced decision-making strategies that provide responsive factories with adaptation and reconfiguration capabilities and advanced complementary scheduling abilities. The aim is to facilitate operational flexibility and increase productivity as well as offer strategic advantages such as analysis of factory development options by simulation. The feasibility of the proposed system is demonstrated by simulation under various experimental settings, among them shop utilization level, due date tightness and breakdown level.

A Performance Comparison between Efficiency and Pheromone Approaches in Dynamic Manufacturing Scheduling

2011 ◽  
pp. 273-298 ◽  
Author(s):  
Paolo Renna
Keyword(s):  
Manufacturing Systems ◽  
Processing Time ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Dynamic Environment ◽  
Performance Comparison ◽  
Coordination Mechanism ◽  
Job Shop Scheduling Problem ◽  
Manufacturing Performance ◽  
Multi Agent

This chapter proposes an innovative coordination mechanism in manufacturing systems by pheromone approach in a multi-agent architecture environment. A pheromone-based coordination mechanism can reduce the communication among agents and decision-making complexity. The chapter focuses on job shop scheduling problem in cellular manufacturing systems. The principal aim is the evaluation of the performance of the proposed approaches compared with the approaches proposed in the literature (benchmark) in order to evidence the improvements. A simulation environment developed in ARENA® package was used to investigate the influence of several parameters on the manufacturing performance. The proposed approaches are tested in a dynamic environment; the simulation scenarios are characterized by the following parameters: inter-arrival, machine breakdowns and processing time efficiency. The simulation results highlighted that the performance of the proposed approaches are very competitive to the benchmark.

An agent-based architecture for production scheduling in dynamic job-shop manufacturing system

2018 ◽  
Vol 66 (6) ◽  
pp. 492-502 ◽  
Author(s):  
Om Ji Shukla ◽  
Gunjan Soni ◽  
Rajesh Kumar ◽  
Sujil A
Keyword(s):  
Production Planning ◽  
Production Scheduling ◽  
Manufacturing System ◽  
Job Shop ◽  
Shop Floor ◽  
Efficient Production ◽  
Planning And Scheduling ◽  
Agent Based ◽  
Production Planning And Scheduling ◽  
Key Issues

Abstract In a highly competitive environment, effective production is one of the key issues which can be addressed by efficient production planning and scheduling in the manufacturing system. This paper develops an agent-based architecture which enables integration of production planning and scheduling. In addition, this architecture will facilitate real time production scheduling as well as provide a multi-agent system (MAS) platform on which multiple agents will interact to each other. A case study of job-shop manufacturing system (JMS) has been considered in this paper for implementing the concept of MAS. The modeling of JMS has been created in SimEvents which integrates an agent-based architecture developed by Stateflow to transform into dynamic JMS. Finally, the agent-based architecture is evaluated using utilization of each machine in the shop floor with respect to time.

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