N∗—an agent-based negotiation algorithm for dynamic scheduling and rescheduling

Chun, Hon Wai; Wong, Rosa S.

doi:10.1016/s1474-0346(03)00019-3

Cited by 30 publications

(14 citation statements)

References 12 publications

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“…The experiments on randomly generated instances with different structures indicate that a tabu search heuristic solution outperforms other algorithms. In order to bridge the gap between theory and practice, a two-stage HFS problem was modeled with specific concerns about machining from the first and second stage [35]. This paper analyzes this problem from a small scope with the worst cases analysis.…”

Section: Hybrid Flow Shop Schedulingmentioning

confidence: 99%

A two-level advanced production planning and scheduling model for RFID-enabled ubiquitous manufacturing

Zhong

Huang

Lan

et al. 2015

Advanced Engineering Informatics

120

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Section: Hybrid Flow Shop Schedulingmentioning

confidence: 99%

A two-level advanced production planning and scheduling model for RFID-enabled ubiquitous manufacturing

Zhong

Huang

Lan

et al. 2015

Advanced Engineering Informatics

120

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“…The set of constraints (2) ensures that an operation does not start before the previous operation of the same job is completed. The set of constraints (3) and (4) ensure that at most one job can be processed by a particular engineer at a time.…”

Section: Constraintsmentioning

confidence: 99%

“…When generating a specific problem set, we first fix the numbers of maintenance jobs, operations in each job, and engineers, then, randomly assign engineers' capabilities (capable operations and corresponding processing times). We assume engineers' labor cost rates on a specific operation are identical 2 . Table I summarizes the configuration of the test problem sets.…”

Section: A Computational Studymentioning

confidence: 99%

Distributed Scheduling for Reactive Maintenance of Complex Systems

Wang

Ghenniwa

Shen

2008

IEEE Trans. Syst., Man, Cybern. C

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/npsi/ctrl?lang=en http://nparc.cisti-icist.nrc-cnrc.gc.ca/npsi/ctrl?lang=fr Access and use of this website and the material on it are subject to the Terms and Conditions set forth at http://nparc.cisti-icist.nrc-cnrc.gc.ca/npsi/jsp/nparc_cp.jsp?lang=en NRC Publications Archive Archives des publications du CNRCThis publication could be one of several versions: author's original, accepted manuscript or the publisher's version. / La version de cette publication peut être l'une des suivantes : la version prépublication de l'auteur, la version acceptée du manuscrit ou la version de l'éditeur. Systems, Man, and Cybernetics, Part C, 38, 2, pp. 269-273, 2008-03-01 Distributed scheduling for reactive maintenance of complex systems Wang, C.; Ghenniwa, H.; Shen, W. IEEE Transactions onhttp://irc.nrc-cnrc.gc.ca Distributed scheduling for reactive maintenance of complex systems NRCC-50278Wang, C.; Ghenniwa, H.; Shen, W. March 2008A version of this document is published in / Une version de ce document se trouve dans: IEEE Transactions on Systems, Man, and Cybernetics, Part C, v. 38, no. 2, 2008, .pp 269-273 The material in this document is covered by the provisions of the Copyright Act, by Canadian laws, policies, regulations and international agreements. Such provisions serve to identify the information source and, in specific instances, to prohibit reproduction of materials without written permission. For more information visit http://laws.justice.gc.ca/en/showtdm/cs/C-42Les renseignements dans ce document sont protégés par la Loi sur le droit d'auteur, par les lois, les politiques et les règlements du Canada et des accords internationaux. Ces dispositions permettent d'identifier la source de l'information et, dans certains cas, d'interdire la copie de documents sans permission écrite. Pour obtenir de plus amples renseignements : http://lois.justice.gc.ca/fr/showtdm/cs/C-42 > REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < Abstract-This paper presents a distributed scheduling algorithm for reactive maintenance of complex systems. The proposed algorithm uses an iterative bidding procedure to assign operations of maintenance jobs to engineers with partially overlapped skill sets. In each round, an unassigned operation is selected based on the overlapping degree of engineers' skill sets on the operation and its average processing time among capable engineers. Engineers' availability and cost information are used to determine the winner of an assignment. The effectiveness of this approach is demonstrated through a computational case study. Prototype implementation and applications to real world domains are discussed.

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“…Agents negotiate on the type of activity, destination location, and the departure time of their communal activities. Chun and Wong [15] presented a generalized model to schedule events dynamically that uses a negotiation mechanism. It is based on an agent-based approach.…”

Section: Introductionmentioning

confidence: 99%

An Organizational-Based Model and Agent-Based Simulation for Co-Traveling at an Aggregate Level

et al. 2017

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Abstract:Carpooling is an environmentally friendly and sustainable emerging traveling mode that enables commuters to save travel time and travel expenses. In order to co-travel, individuals or agents need to communicate, interpret information, and negotiate to achieve co-operation to find matching partners. This paper offers the scheme of a carpooling model for a set of candidate carpoolers. The model is interpreted using an agent-based simulation to analyze several effects of agents' interaction and behavior adaptations. Through communication and negotiation processes, agents can reach dynamic contracts in an iterative manner. The start of the negotiation process relies on the agents' intention to emit an invitation for carpooling. The realization of the negotiation process depends significantly on the departure time choice, on the agents' profile, and on route optimization. The schedule or agenda adaptation relies on the preferences among the realistic schedules of the agents and usually depends on both the participation of the trip and on the time of day. From the considerations, it is possible to reveal the actual representation of the possible carpoolers during the simulated period. Experiments demonstrate the nearly-polynomial relationship between computation time and the number of agents.

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N∗—an agent-based negotiation algorithm for dynamic scheduling and rescheduling

Cited by 30 publications

References 12 publications

A two-level advanced production planning and scheduling model for RFID-enabled ubiquitous manufacturing

A two-level advanced production planning and scheduling model for RFID-enabled ubiquitous manufacturing

Distributed Scheduling for Reactive Maintenance of Complex Systems

An Organizational-Based Model and Agent-Based Simulation for Co-Traveling at an Aggregate Level

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