Work

On solution discovery via reconfiguration

Year: 2025

Type: article

Abstract: The dynamics of real-world applications and systems require efficient methods for improving infeasible solutions or restoring corrupted ones by making modifications to the current state of a system in a restricted way. We propose a new framework of solution discovery via reconfiguration for constructing a feasible solution for a given problem by executing a sequence of small modifications starting from a given state or configuration. Our framework integrates and formalizes different aspects of classical local search, reoptimization, and combinatorial reconfiguration. We exemplify our framework on a multitude of fundamental combinatorial problems, namely Vertex Cover , Independent Set , Dominating Set , and Coloring . We study the classical as well as the parameterized complexity of the solution discovery variants of those problems and explore the boundary between tractable and intractable instances.

Source: Journal of Computer and System Sciences

DOI: 10.1016/j.jcss.2025.103747

Authors: Michael R. Fellows, Mario Grobler, Nicole Megow, Amer E. Mouawad, Vijayaragunathan Ramamoorthi, Frances A. Rosamond, Daniel Schmand, Sebastian Siebertz

Institutions: Lebanese American University, University of Bremen, American University of Beirut

Language: English

Topic: Advanced Graph Theory Research

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $2,610

Funders: Alexander von Humboldt-Stiftung, Universität Bremen

OpenAlex ID: W7114771443

FWCI:

Cites: 57

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