A Market-Based Optimization Algorithm for Distributed Systems

Zhiling Guo (), Gary J. Koehler () and Andrew B. Whinston ()
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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

Management Science, 2007, vol. 53, issue 8, 1345-1358

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.

Keywords: market-based; decomposition; algorithm; distributed systems; resource allocation (search for similar items in EconPapers)
Date: 2007
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Citations: View citations in EconPapers (9)

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