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    Simulation-Based Auction Protocol for Resource Scheduling Problems

    Source: Journal of Construction Engineering and Management:;2012:;Volume ( 138 ):;issue: 001
    Author:
    H. Taghaddos
    ,
    S. AbouRizk
    ,
    Y. Mohamed
    ,
    U. Hermann
    DOI: 10.1061/(ASCE)CO.1943-7862.0000399
    Publisher: American Society of Civil Engineers
    Abstract: Resource scheduling, or the allocation of resources over time, is a challenging problem in large-scale or multiple-project environments. Traditional network scheduling techniques are ineffective in modeling the dynamic nature and resource interactions of large or multiunit projects. This paper presents a simulation-based auction protocol (SBAP) to solve resource scheduling problems in large-scale construction projects. SBAP is a hybrid framework that integrates multi agent resource allocation (MARA) in a simulation environment. SBAP deploys a centralized resource allocation approach, referred to as an auction protocol, whereby agents bid on different combinations of resources at the start of a simulation cycle. Agents attempt to improve their individual welfare by acquiring a combination of resources; an auctioneer looks at the entire system and allocates resources to the agents using a combinatorial algorithm to maximize an overall objective function (e.g., maximizing the system’s revenue or minimizing total costs). The auction is repeated on a regular basis. Simulation is also employed in large-scale projects to track the availability of resources, capture and release the resources, and satisfy constraints of the problem. This paper demonstrates the architecture of the SBAP framework and discusses implementation of SBAP in a real case study of crane allocation in an industrial project.
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      Simulation-Based Auction Protocol for Resource Scheduling Problems

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    contributor authorH. Taghaddos
    contributor authorS. AbouRizk
    contributor authorY. Mohamed
    contributor authorU. Hermann
    date accessioned2017-05-08T21:39:31Z
    date available2017-05-08T21:39:31Z
    date copyrightJanuary 2012
    date issued2012
    identifier other%28asce%29co%2E1943-7862%2E0000406.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/58559
    description abstractResource scheduling, or the allocation of resources over time, is a challenging problem in large-scale or multiple-project environments. Traditional network scheduling techniques are ineffective in modeling the dynamic nature and resource interactions of large or multiunit projects. This paper presents a simulation-based auction protocol (SBAP) to solve resource scheduling problems in large-scale construction projects. SBAP is a hybrid framework that integrates multi agent resource allocation (MARA) in a simulation environment. SBAP deploys a centralized resource allocation approach, referred to as an auction protocol, whereby agents bid on different combinations of resources at the start of a simulation cycle. Agents attempt to improve their individual welfare by acquiring a combination of resources; an auctioneer looks at the entire system and allocates resources to the agents using a combinatorial algorithm to maximize an overall objective function (e.g., maximizing the system’s revenue or minimizing total costs). The auction is repeated on a regular basis. Simulation is also employed in large-scale projects to track the availability of resources, capture and release the resources, and satisfy constraints of the problem. This paper demonstrates the architecture of the SBAP framework and discusses implementation of SBAP in a real case study of crane allocation in an industrial project.
    publisherAmerican Society of Civil Engineers
    titleSimulation-Based Auction Protocol for Resource Scheduling Problems
    typeJournal Paper
    journal volume138
    journal issue1
    journal titleJournal of Construction Engineering and Management
    identifier doi10.1061/(ASCE)CO.1943-7862.0000399
    treeJournal of Construction Engineering and Management:;2012:;Volume ( 138 ):;issue: 001
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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