Polynomial Time Algorithms for Integer Programming and Unbounded Subset Sum in the Total Regime
Divesh Aggarwal, Antoine Joux, Miklos Santha, Karol W\k{e}grzycki

TL;DR
This paper presents polynomial-time algorithms for solving certain instances of the Unbounded Subset Sum and Integer Linear Programming problems when solutions are guaranteed to exist, especially for large target values.
Contribution
It introduces polynomial-time algorithms for USS and ILPE in the total regime, extending the concept of totality and the diagonal Frobenius number to these problems.
Findings
Polynomial-time solution for USS when b exceeds the Frobenius number.
Extension of results to Integer Linear Programming with Equalities.
Algorithm bounds nearly match recent existential bounds.
Abstract
The Unbounded Subset Sum (USS) problem is an NP-hard computational problem where the goal is to decide whether there exist non-negative integers such that , where are distinct positive integers with dividing . The problem can be solved in pseudopolynomial time, while specialized cases, such as when exceeds the Frobenius number of simplify to a total problem where a solution always exists. This paper explores the concept of totality in USS. The challenge in this setting is to actually find a solution, even though we know its existence is guaranteed. We focus on the instances of USS where solutions are guaranteed for large . We show that when is slightly greater than the Frobenius number, we can find the solution to USS in polynomial time. We then…
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Taxonomy
TopicsScheduling and Optimization Algorithms · Optimization and Search Problems · Complexity and Algorithms in Graphs
