- A Path to the Arrow-Debreu Competitive Market Equilibrium Yinyu Ye (yinyu-yestanford.edu) Abstract: We present polynomial-time interior-point algorithms for solving the Fisher and Arrow-Debreu competitive market equilibrium problems with linear utilities and $n$ players. Both of them have the arithmetic operation complexity bound of $O(n^4\log(1/\epsilon))$ for computing an $\epsilon$-equilibrium solution. If the problem data are rational numbers and their bit-length is $L$, then the bound to generate an exact solution is $O(n^4L)$ which is in line with the best complexity bound for linear programming of the same dimension and size. This is a significant improvement over the previously best bound $O(n^8\log(1/\epsilon))$ for approximating the two problems using other methods. The key ingredient to derive these results is to show that these problems admit convex optimization formulations, efficient barrier functions and fast rounding techniques. We also present a continuous path leading to the set of the Arrow-Debreu equilibrium, similar to the central path developed for linear programming interior-point methods. This path is derived from the weighted logarithmic utility and barrier functions and the Brouwer fixed-point theorem. The defining equations are bilinear and possess some primal-dual structure for the application of the Newton-based path-following method. Keywords: Analytic Center, Market Equilibria, , Complexity Category 1: Other Topics (Game Theory ) Category 2: Linear, Cone and Semidefinite Programming (Linear Programming ) Category 3: Complementarity and Variational Inequalities Citation: Working Paper posted February/23/04, revised final version July 15, 2005; to appear in Math Programming 2006. Download: [PDF]Entry Submitted: 07/28/2006Entry Accepted: 07/28/2006Entry Last Modified: 07/28/2006Modify/Update this entry Visitors Authors More about us Links Subscribe, Unsubscribe Digest Archive Search, Browse the Repository Submit Update Policies Coordinator's Board Classification Scheme Credits Give us feedback Optimization Journals, Sites, Societies Optimization Online is supported by the Mathematical Programming Society and by the Optimization Technology Center.