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

Ying Zi Wei, Yi Jun Feng, Kan Feng Gu
2011 Advanced Engineering Forum  
This paper builds an efficient agent-based flexible scheduling for real-world manufacturing systems.  ...  CNP is introduced to allow the agents to cooperate and coordinate their local schedules in order to find globally near-optimal robust schedules.  ...  Ant colony intelligence in flexible job shop scheduling Dorigo et al. firstly introduced Ant Colony Optimization (ACO) for solving the TSP which is based on ant foraging.  ... 
doi:10.4028/www.scientific.net/aef.2-3.608 fatcat:nyiryenfkjgtrjmaqlbfmyshr4

An Efficient Ant Colony Optimization Algorithm For Multiobjective Flow Shop Scheduling Problem

Ahmad Rabanimotlagh
2011 Zenodo  
In this paper an ant colony optimization algorithm is developed to solve the permutation flow shop scheduling problem.  ...  Here this problem is optimized considering two criteria, makespan and total flow time. Then the results are compared with the ones obtained by previously developed algorithms.  ...  Author deployed a hybrid ant colony optimization algorithm to minimize total flow time in a flow shop sequence dependent group scheduling problem.  ... 
doi:10.5281/zenodo.1077155 fatcat:shwgecthenfhrb2yv2y4ohedom

Applying Ant Colony Optimisation (ACO) algorithm to dynamic job shop scheduling problems

Rong Zhou, Heow Pueh Lee, Andrew Y.C. Nee
2008 International Journal of Manufacturing Research  
Ant Colony Optimization (ACO) is applied to two dynamic job scheduling problems, which have the same mean total workload but different dynamic levels and disturbing severity.  ...  Its performances are statistically analysed and the effects of its adaptation mechanism and parameters such as the minimal number of iterations and the size of searching ants are studied.  ...  Ant Colony Optimization (ACO) is another metaheuristic proposed by and it has been applied to JSSP by Colorni et al. (1994) and van der Zwaan and Marques (1999) .  ... 
doi:10.1504/ijmr.2008.019212 fatcat:2gmox3diq5bg5p5itfub2rohrm

Multi-objective automated guided vehicle scheduling based on MapReduce framework

W. Shi, D.B. Tang, P. Zou
2021 Advances in Production Engineering & Management  
By using a speed control strategy, we were able to detect the overlap path and the conflict time.  ...  To solve this problem, we proposed a multi-objective scheduling model based on total driving distance and waiting time, and used the A* path planning algorithm to search the shortest path of AGV.  ...  Dynamic shop floor re-scheduling approach inspired by a neuroendocrine regulation mechanism, Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, Vol. 229  ... 
doi:10.14743/apem2021.1.383 fatcat:3mifyaaazjgabenv2xx7yi2jfu

Job Shop Scheduling Methods Review [chapter]

Borut Buchmeister, Iztok Palcic, Robert Ojstersek
2021 DAAAM International Scientific Book 2013  
In this paper, an overview of scheduling methods for a job shop and a discussion about their applicability are given.  ...  Conventional optimization methods are insufficient for large problems in terms of solution time.  ...  Ant Colony Optimization (ACO) Ant Colony Optimization has been proposed in the literature as a new metaheuristic approach to solve difficult combinatorial optimization problems.  ... 
doi:10.2507/daaam.scibook.2021.01 fatcat:hyowgczzbrfizk36mblhn3f2e4

Improved Ant Colony Optimization for Multi-Resource Job Shop Scheduling: A Special Case of Transportation

BEHMANESH REZA, RAHIMI IMAN
2021 ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH  
Among the scheduling problems, job shop scheduling problem (JSP) is a common scheduling model that is applied in real-world industries.  ...  Ant Colony Optimization Using Lazy Ant Approach for Grid Scheduling Problem; Future Generation Computer Systems,Vol. 60, pp. 78-89; [22] Xiang, W., Yin, J., Lim, G. (2015), An Ant Colony Optimization  ... 
doi:10.24818/18423264/55.4.21.18 fatcat:wxwwqxhe4ncc7af7ifm2po4dny

Order Management in Non-Hierarchical Production Networks using Genetic Algorithms [chapter]

Horst Meier, Tobias Teich, Harald Schallner
2002 IFIP Advances in Information and Communication Technology  
The global economy of the 21st century will be characterized by competing corporate networks rather than by competing enterprises.  ...  The purpose of this paper is to put forward a specific functionality to schedule production considering constraint networks.  ...  complexity of real-world shop floor scheduling.  ... 
doi:10.1007/978-0-387-35492-7_35 fatcat:gxyqml6zczbwxmnooh55hnugza

Bio-inspired multi-agent systems for reconfigurable manufacturing systems

Paulo Leitão, José Barbosa, Damien Trentesaux
2012 Engineering applications of artificial intelligence  
Acknowledgments The experimental work was performed by a project team, including Nadine Zbib, Cyrille Pach, Yves Sallez, Thierry Berger, with the help and support of the AIP-PRIMECA team.  ...  Shop floor layout, which requires optimizing the shop floor layout in order to minimize transport time and to minimize transport distances, in situations where shop floor resources move physically.  ...  Planning and scheduling, in which the goal is to find the most current optimized plans and schedules, while taking the product demands and the capabilities of the shop floor resources into consideration  ... 
doi:10.1016/j.engappai.2011.09.025 fatcat:ldfomxk5r5fm7mkzhj6efpchsa

Dynamic Impact for Ant Colony Optimization algorithm [article]

Jonas Skackauskas, Tatiana Kalganova, Ian Dear, Mani Janakram
2020 arXiv   pre-print
This paper proposes an extension method for Ant Colony Optimization (ACO) algorithm called Dynamic Impact.  ...  This proposed method is tested against complex real-world Microchip Manufacturing Plant Production Floor Optimization (MMPPFO) problem, as well as theoretical benchmark Multi-Dimensional Knapsack problem  ...  We are using Ant Colony Optimization (ACO) metaheuristic algorithm to solve real world Microchip Manufacturing Plant Production Floor Optimization (MMPPFO) problem and theoretical Multi-Dimensional Knapsack  ... 
arXiv:2002.04099v1 fatcat:p5a5cbisgzg7vgvknov7a5bymm

Concurrent Solution of WATC Scheduling with WPPW Due Date Assignment for Environmentally Weighted Customers, Jobs and Services Using SA and its Hybrid

Halil Ibrahim Demir, Caner Erden, Abdullah Hulusi Kökçam, Ozer Uygun
2019 Periodicals of Engineering and Natural Sciences (PEN)  
, [19] , agent-based [20] , [21] and ant colony optimization [22] .  ...  So, it is almost impossible to find optimal results in real applications for IPPS [11] .  ... 
doi:10.21533/pen.v6i2.186 fatcat:2kgsz3yps5hm3jf6ktuj6tnmbm

A Framework for Implementing Lean Manufacturing System in Small and Medium Enterprises

Jirapat Wanitwattanakosol, Apichat Sopadang
2011 Applied Mechanics and Materials  
Phase 2 performs a just in time production schedule by using ant colony optimization technique combines with a simulation tool.  ...  The result shows how to combine lean concept with simulation optimization, the step of this framework to obtain the optimization solution.  ...  Ant colony optimization (ACO) The first combinatorial optimization problem which was solved by ACO is the travelling salesman problem (TSP).  ... 
doi:10.4028/www.scientific.net/amm.110-116.3997 fatcat:vmdf3gtxlfgi5ccq5yaqrsqjvm

Job shop scheduling by pheromone approach in a dynamic environment

P. Renna
2010 International journal of computer integrated manufacturing (Print)  
The paper concerns the job shop scheduling problem in cellular manufacturing systems; the schedule is created by a pheromone based approach.  ...  Job shop scheduling problem is a NP-hard problem, therefore the objective is to create a schedule that satisfies all the constraints while taking as little overall time as possible.  ...  In the real world, ants (initially) wander randomly, and upon finding food return to their colony while laying down pheromone trails.  ... 
doi:10.1080/09511921003642170 fatcat:ypubtbdgjjazzegtpdpzsaivoe

Task scheduling of AGV in FMS using non-traditional optimization techniques

P. Udhayakumar, S. Kumanan
2010 International Journal of Simulation Modelling  
This paper addresses multi objective task scheduling of AGV in a flexible manufacturing environment using nontraditional optimization algorithms.  ...  In recent years, random search algorithms have been attempted for scheduling. Most of the research has been emphasized only on single objective optimization.  ...  Most of the real world-scheduling problems involve simultaneous optimization of multiple objectives.  ... 
doi:10.2507/ijsimm09(1)3.139 fatcat:elsel5a7yrggbnqpcnjnelg7wa

Reactive business processes for factory automation

Domnic Savio, Stamatis Karnouskos, Luciana Moreira Sa de Souza, Vlad Trifa, Dominique Guinard, Patrik Spiess
2009 2009 7th IEEE International Conference on Industrial Informatics  
The work presented here shows directions to achieve this dynamism by means of simulation, state identification and close coupling of real world and business systems.  ...  Business continuity needs to be guaranteed, while changes at the shop floor should happen onthe-fly without stopping the production process.  ...  This helps enterprise systems to dynamically adapt to changes in the shop-floor, to reduce the gap between the real world and its digital representation, and also to optimize business processes.  ... 
doi:10.1109/indin.2009.5195874 fatcat:edbfk2evtrctvk5ttk35dwjhoa

Multi-agent and Bargaining-game-based Real-time Scheduling for Internet of Things-enabled Flexible Job Shop

Jin Wang, Yingfeng Zhang, Yang Liu, Naiqi Wu
2018 IEEE Internet of Things Journal  
Thus, how to schedule the manufacturing shop floor for achieving such a goal is very challenging.  ...  Differing from traditional dynamic scheduling strategies, the proposed strategy optimally assigns tasks to machines according to their real-time status.  ...  They developed a hybrid MAS negotiation mechanism and proposed an ant colony optimization approach.  ... 
doi:10.1109/jiot.2018.2871346 fatcat:ii3ahye2yjgipkxx65g6xb44sq
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