A Market-Oriented Programming Environment and its Application to Distributed Multicommodity Flow Problems

Wellman, Michael P.

doi:10.1613/jair.2

Cited by 342 publications

(168 citation statements)

References 24 publications

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“…The total investment into the supply network is redistributed at each layer. The process of redistribution of market investment is executed by the MOP algorithm [5] described in section 4.1. Movement of resources thus is in two directions; primary resources rented out by consumers move from the investment layer to the final product layer from where it is used to procure input production resources from the layer preceding it.…”

Section: Market Value Propagation Protocol(mvpp)mentioning

confidence: 99%

“…While a number of algorithms have been constructed to find computable general equilibrium [4,5], our contribution lies in applying the concept to generate procurement plans for multilayered convergent network intended to preserve autonomy of enterprises in the network. We focus on the protocol that generates procurement budgets for enterprises in the supply network making use of quantified supplier preferences and input resource valuations assumed to already have been computed by enterprise agents.…”

Section: Introductionmentioning

confidence: 99%

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A Study on Market-based Strategic Procurement Planning in Convergent Supply Networks

Opadiji

Kaihara

2009

Transactions of ISCIE

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We present a market-based decentralized approach which uses a market-oriented programming algorithm to obtain Pareto-optimal allocation of resources traded among agents which represent enterprise units in a supply network. The proposed method divides the network into a series of Walrsian markets in order to obtain procurement budgets for enterprises in the network. An interaction protocol based on market value propagation is constructed to coordinate the flow of resources across the network layers. The method mitigates the effect of product complementarity in convergent network by allowing for enterprises to hold private valuations of resources in the markets.

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Section: Market Value Propagation Protocol(mvpp)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Study on Market-based Strategic Procurement Planning in Convergent Supply Networks

Opadiji

Kaihara

2009

Transactions of ISCIE

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“…Wellman (1993) considers a market-oriented programming approach to distributed problem solving by deriving the activities and resource allocations for a set of computational agents. He considers the multicommodity flow problem and shows that careful construction of the decision process, according to economic principles, can lead to efficient distributed resource allocation, and that the behavior of the system can be meaningfully analyzed in economic terms.…”

Section: Models For Supply Chains In E-businessmentioning

confidence: 99%

Models for Supply Chains in E-Business

2003

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S upply chain management is likely to play an important role in the digital economy. In this paper, we first describe major issues in traditional supply chain management. Next, we focus our attention on the supply chain issues of visibility, supplier relationships, distribution and pricing, customization, and real-time decision technologies that have risen to importance with the prevalence of e-business. We present an overview of relevant analytical research models that have been developed in these areas, discuss their contributions, and conclude with a discussion on future modeling opportunities in this area.

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“…This market mechanism leads to an equitable temperature distribution in the system 135]. Other domains where market mechanisms were successfully applied include purchasing memory in an operating systems 53], allocating virtual circuits 89], \stealing" unused CPU cycles in a network of computers 79,269], predicting option futures in nancial markets 214], and numerous scheduling and distributed resource allocation problems 159,165,245,255,275,276].…”

Section: Computational Economicsmentioning

confidence: 99%

Theory of Collective Intelligence

Wolpert

2004

Collectives and the Design of Complex Systems

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This paper surveys the emerging science of how to design a \COllective INtelligence" (COIN). A COIN is a large multi-agent system where: i) There is little to no centralized, personalized communication and/or control. ii) There is a provided world utility function that rates the possible histories of the full system.In particular, we a r e i n terested in COINs in which e a c h a g e n t runs a reinforcement learning (RL) algorithm. The conventional approach to designing large distributed systems to optimize a world utility does not use agents running RL algorithms. Rather, that approach begins with explicit modeling of the dynamics of the overall system, followed by detailed hand-tuning of the interactions between the components to ensure that they \cooperate" as far as the world utility i s concerned. This approach is labor-intensive, often results in highly nonrobust systems, and usually results in design techniques that have limited applicability. In contrast, we w i s h t o s o l v e the COIN design problem implicitly, via the \adaptive" character of the RL algorithms of each of the agents. This approach i n troduces an entirely new, profound design problem: Assuming the RL algorithms are able to achieve high rewards, what reward functions for the individual agents will, when pursued by those agents, result in high world utility? In other words, what reward functions will best ensure that we d o n o t have phenomena like t h e tragedy of the commons, Braess's paradox, or the liquidity trap? Although still very young, research speci cally concentrating on the COIN design problem has already resulted in successes in arti cial domains, in particular in packet-routing, the leader-follower problem, and in variants of Arthur's El Farol bar problem. It is expected that as it matures and draws upon other disciplines related to COINs, this research will greatly expand the range of tasks addressable by human engineers. Moreover, in addition to drawing on them, such a fully developed science of COIN design may provide much insight into other already established scienti c elds, such as economics, game theory, and population biology.

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A Market-Oriented Programming Environment and its Application to Distributed Multicommodity Flow Problems

Cited by 342 publications

References 24 publications

A Study on Market-based Strategic Procurement Planning in Convergent Supply Networks

A Study on Market-based Strategic Procurement Planning in Convergent Supply Networks

Models for Supply Chains in E-Business

Theory of Collective Intelligence

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