TY - GEN
T1 - Polynomial Time Algorithms to Find an Approximate Competitive Equilibrium for Chores
AU - Boodaghians, Shant
AU - Chaudhury, Bhaskar Ray
AU - Mehta, Ruta
N1 - Publisher Copyright:
Copyright © 2022 by SIAM.
PY - 2022
Y1 - 2022
N2 - Competitive equilibrium with equal income (CEEI) is considered one of the best mechanisms to allocate a set of items among agents fairly and efficiently. In this paper, we study the computation of CEEI when items are chores that are disliked (negatively valued) by agents, under 1-homogeneous and concave utility functions which includes linear functions as a subcase. It is well-known that, even with linear utilities, the set of CEEI may be non-convex and disconnected, and the problem is PPAD-hard in the more general exchange model. In contrast to these negative results, we design a FPTAS: A polynomial-time algorithm to compute "-approximate CEEI where the running-time depends polynomially on 1 ". Our algorithm relies on the recent characterization due to Bogomolnaia et al. (2017) of the CEEI set as exactly the KKT points of a non-convex minimization problem that have all coordinates non-zero. Due to this non-zero constraint, näive gradient-based methods fail to find the desired local minima as they are attracted towards zero. We develop an exterior-point method that alternates between guessing non-zero KKT points and maximizing the objective along supporting hyperplanes at these points. We show that this procedure must converge quickly to an approximate KKT point which then can be mapped to an approximate CEEI; this exterior point method may be of independent interest. When utility functions are linear, we give explicit procedures for finding the exact iterates, and as a result show that a stronger form of approximate CEEI can be found in polynomial time. Finally, we note that our algorithm extends to the setting of un-equal incomes (CE), and to mixed manna with linear utilities where each agent may like (positively value) some items and dislike (negatively value) others.
AB - Competitive equilibrium with equal income (CEEI) is considered one of the best mechanisms to allocate a set of items among agents fairly and efficiently. In this paper, we study the computation of CEEI when items are chores that are disliked (negatively valued) by agents, under 1-homogeneous and concave utility functions which includes linear functions as a subcase. It is well-known that, even with linear utilities, the set of CEEI may be non-convex and disconnected, and the problem is PPAD-hard in the more general exchange model. In contrast to these negative results, we design a FPTAS: A polynomial-time algorithm to compute "-approximate CEEI where the running-time depends polynomially on 1 ". Our algorithm relies on the recent characterization due to Bogomolnaia et al. (2017) of the CEEI set as exactly the KKT points of a non-convex minimization problem that have all coordinates non-zero. Due to this non-zero constraint, näive gradient-based methods fail to find the desired local minima as they are attracted towards zero. We develop an exterior-point method that alternates between guessing non-zero KKT points and maximizing the objective along supporting hyperplanes at these points. We show that this procedure must converge quickly to an approximate KKT point which then can be mapped to an approximate CEEI; this exterior point method may be of independent interest. When utility functions are linear, we give explicit procedures for finding the exact iterates, and as a result show that a stronger form of approximate CEEI can be found in polynomial time. Finally, we note that our algorithm extends to the setting of un-equal incomes (CE), and to mixed manna with linear utilities where each agent may like (positively value) some items and dislike (negatively value) others.
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M3 - Conference contribution
AN - SCOPUS:85126595825
T3 - Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms
SP - 2285
EP - 2302
BT - ACM-SIAM Symposium on Discrete Algorithms, SODA 2022
PB - Association for Computing Machinery
T2 - 33rd Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2022
Y2 - 9 January 2022 through 12 January 2022
ER -