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A Market-Based Optimization Algorithm for Distributed Systems

Author

Listed:
  • Zhiling Guo

    (Department of Information Systems, University of Maryland, Baltimore County, Baltimore, Maryland 21250)

  • Gary J. Koehler

    (Department of Decision and Information Sciences, Warrington College of Business Administration, University of Florida, Gainesville, Florida 32611)

  • Andrew B. Whinston

    (Department of Information, Risk, and Operations Management, McCombs School of Business, The University of Texas at Austin, Austin, Texas 78712)

Abstract

In this paper, a market-based decomposition method for decomposable linear systems is developed. The solution process iterates between a master problem that solves the market-matching problem, and subproblems that solve the agents' bundle-determination problems. Starting from any initial price and feasible allocation, system optimality can be achieved under a dynamic market-trading algorithm in a finite number of trades. The final market-clearing prices are discovered by this market trading and an efficient allocation is achieved by direct, wealth-improving resource exchanges among self-interested agents. Certain types of strategic behavior by the agents and a dealer in the marketplace are studied as well. Our proposed market mechanism addresses price dynamics, incentive issues, and economic transactions of real-world, distributed decision-making situations more realistically than traditional decomposition approaches. In addition, it can be operated in both synchronous and asynchronous environments. We provide a market-based paradigm for decentralized problem solving and information processing that can be easily implemented to support real-time optimization of distributed systems.

Suggested Citation

  • Zhiling Guo & Gary J. Koehler & Andrew B. Whinston, 2007. "A Market-Based Optimization Algorithm for Distributed Systems," Management Science, INFORMS, vol. 53(8), pages 1345-1358, August.
    • Handle: RePEc:inm:ormnsc:v:53:y:2007:i:8:p:1345-1358
    DOI: 10.1287/mnsc.1060.0690
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    References listed on IDEAS

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    Cited by:

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    3. Zhiling Guo & Gary J. Koehler & Andrew B. Whinston, 2012. "A Computational Analysis of Bundle Trading Markets Design for Distributed Resource Allocation," Information Systems Research, INFORMS, vol. 23(3-part-1), pages 823-843, September.
    4. Lai, Minghui & Cai, Xiaoqiang & Hu, Qian, 2017. "An iterative auction for carrier collaboration in truckload pickup and delivery," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 107(C), pages 60-80.
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    7. Andor Goetzendorff & Martin Bichler & Pasha Shabalin & Robert W. Day, 2015. "Compact Bid Languages and Core Pricing in Large Multi-item Auctions," Management Science, INFORMS, vol. 61(7), pages 1684-1703, July.
    8. Martin Bichler & Pasha Shabalin & Georg Ziegler, 2013. "Efficiency with Linear Prices? A Game-Theoretical and Computational Analysis of the Combinatorial Clock Auction," Information Systems Research, INFORMS, vol. 24(2), pages 394-417, June.
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