Opadiji, JayeolaKaihara, Toshiya2019-06-032019-06-032007http://hdl.handle.net/123456789/2049Finding 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.enResource AllocationVirtual Enterprise NetworkOptimizationSupply NetworksArticle