A study on resource allocation optimization in a multi-commodity virtual enterprise network
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Date
2007
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Published by the Graduate School of Science and Technology, Kobe University, Japan.
Abstract
Finding an optimal solution to various constrained optimization problems in the supply network of
organizations is clearly a Herculean task considering the fact that some of the objectives to be optimized
have conflicting requirements. A popular method used in tackling issues aimed at improving the
performance of a supply network is to focus on a particular planning horizon and explore activities where
improvements can be made. Optimization problems within a supply network vary from strategic to
operational domains and a number of models have been developed to address these issues including
probabilistic models, mathematical algorithms and some meta-heuristic methodologies. We propose a
strategic decision support model based on Multi-Agent System (MAS) paradigm to find a pareto-optimal
resource allocation among a group of trading agents in a multi-commodity market scenario. We employ the
price mechanism model in microeconomics to create a trading floor for a set of reactive agents to search for
a solution to a resource allocation problem in a virtual enterprise network. While the concept of Competitive
General Equilibrium (CGE) is not new in the neo-classical economic domain, its application to solving
resource allocation problem within a supply chain structure may not be as common. We first study some
existing algorithms for CGE based on the Walrasian market model and then introduce an adaptation of the
Market-Oriented Programming (MOP) paradigm to the supply network problem. We compare the
performance of these algorithms and discuss application areas of the competitive market based approach.
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Keywords
Resource Allocation, Virtual Enterprise Network, Optimization, Supply Networks