Achieving robust optimization in multi-agent systems through iterative constraint approximation
Paper Title:
A cutting-surface consensus approach for distributed robust optimization of multi-agent systems
Published on:
7 September 2023
Primary Category:
Optimization and Control
Paper Authors:
Jun Fu,
Xunhao Wu
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Key Details
Proposes distributed cutting-surface method for robust convex optimization of multi-agent systems
Guarantees convergence and feasibility without differentiability assumptions
Introduces approximated problem with restricted constraints
Develops distributed termination algorithm based on consensus and optimality
Proves finite-time convergence to feasible solution
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AI generated summary
Achieving robust optimization in multi-agent systems through iterative constraint approximation
This paper proposes an iterative distributed optimization method to achieve robust solutions for multi-agent systems with uncertainty. The key idea is to iteratively approximate the problem by gradually tightening constraints and adding cutting surfaces. This balances optimality and feasibility without requiring special constraint structures. The approach converges to an approximately optimal and feasible solution within a finite number of iterations.
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