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Journal of Heuristics

, Volume 22, Issue 5, pp 727–757 | Cite as

Iterated local search with Trellis-neighborhood for the partial Latin square extension problem

  • Kazuya Haraguchi
Article

Abstract

A partial Latin square (PLS) is a partial assignment of n symbols to an \(n\times n\) grid such that, in each row and in each column, each symbol appears at most once. The PLS extension problem is an NP-hard problem that asks for a largest extension of a given PLS. We consider the local search such that the neighborhood is defined by (pq)-swap , i.e., the operation of dropping exactly p symbols and then assigning symbols to at most q empty cells. As a fundamental result, we provide an efficient \((p,\infty )\)-neighborhood search algorithm that finds an improved solution or concludes that no such solution exists for \(p\in \{1,2,3\}\). The running time of the algorithm is \(O(n^{p+1})\). We then propose a novel swap operation, Trellis-swap, which is a generalization of (pq)-swap with \(p\le 2\). The proposed Trellis-neighborhood search algorithm runs in \(O(n^{3.5})\) time. The iterated local search (ILS) algorithm with Trellis-neighborhood is more likely to deliver a high-quality solution than not only ILSs with \((p,\infty )\)-neighborhood but also state-of-the-art optimization solvers such as IBM ILOG CPLEX and LocalSolver.

Keywords

Partial Latin square extension problem Maximum independent set problem Metaheuristics Local search 

Notes

Acknowledgments

We gratefully acknowledge very careful and detailed comments given by anonymous reviewers. This work is partially supported by JSPS KAKENHI Grant Number 25870661.

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Faculty of CommerceOtaru University of CommerceOtaruJapan

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