Title
Iterated Local Search For Consecutive Block Minimization
Abstract
A 1-block in a binary matrix is any maximal sequence of 1s occurring consecutively in the same row. Consecutive block minimization (CBM) requires a permutation of the matrix columns that minimizes the number of 1-blocks. CBM is NP-hard for matrices with a maximum of two 1s per row and an arbitrary number of 1s per column. First, we prove that it is NP-hard even when it is restricted to binary matrices having a maximum of two 1s per row and a maximum of three 1s per column. In these circumstances, a reasonable and traditional approach to solve the problem is to design a heuristic capable of finding good configurations within acceptable computation times. This paper proposes an Iterated Local Search (ILS) metaheuristic. A binary matrix satisfies the strong consecutive ones property (is strongly C1P) if its non-zero entries occur consecutively in each row. It is C1P if there is a permutation of its columns such that the resulting matrix is strongly C1P. In this study, two necessary conditions for a binary matrix to be C1P are provided, each allowing to define a neighborhood for local search (LS). In addition, a third large-scale neighborhood is proposed where the local optimal solution can be directly obtained by solving a Traveling Salesman Problem (TSP). It is noteworthy that the three neighborhoods are being proposed for the first time. The ILS algorithm is tested on a dataset from the OR-library, composed of thirty large-scale set covering instances of varying sizes and densities. Comparison with two TSP solvers as well as with a recently published metaheuristic, from both accuracy and computing time points of view, allows to conclude that the proposed method competes favorably with the methods available in the literature.
Year
DOI
Venue
2021
10.1016/j.cor.2021.105273
COMPUTERS & OPERATIONS RESEARCH
Keywords
DocType
Volume
Consecutive block minimization, Iterated local search, Large-scale neighborhood, Traveling salesman problem solver
Journal
131
ISSN
Citations 
PageRank 
0305-0548
0
0.34
References 
Authors
0
1
Name
Order
Citations
PageRank
Salim Haddadi100.34