Variable neighbourhood search: methods and applications

Abstract

Variable neighbourhood search (VNS) is a metaheuristic, or a framework for building heuristics, based upon systematic changes of neighbourhoods both in descent phase, to find a local minimum, and in perturbation phase to emerge from the corresponding valley. It was first proposed in 1997 and has since then rapidly developed both in its methods and its applications. In the present paper, these two aspects are thoroughly reviewed and an extensive bibliography is provided. Moreover, one section is devoted to newcomers. It consists of steps for developing a heuristic for any particular problem. Those steps are common to the implementation of other metaheuristics.

Cooperative liner shipping network design by means of a combinatorial auction

“…The SSSCR is solved by a heuristic based on variable neighborhood search (Hansen et al 2008). An overview of the variable neighborhood search (VNS) at hand is given by Algorithm 1.…”

A quadtree-based allocation method for a class of large discrete Euclidean location problems

“…Similarly k x and k y can be determined as cor [5] cor [10] cor [15] cor [20] cor [16] cor [21] cor [11] cor [6] cor [1] cor [2] cor [7] cor [17] cor [22] cor [12] cor [3] cor [18] cor [23] cor [8] cor [13] cor [4] cor [19] cor [24] cor [9] cor [14] x…”

“…In this method, the numbering system is slightly different with the original quadtree system. In level 1, there are 4 quads (1-0, 1-1, 1-2, and 1-3) whereas in level 2 there are 16 quads (2-0, ..., [2][3][4][5][6][7][8][9][10][11][12][13][14][15] …”

Designer-driven 3D buildings generated using Variable Neighborhood Search

“…All the three BAF modules are implemented as configurable variants of a modified Variable Neighborhood Search (VNS) metaheuristic algorithm [22]. VNS is an etective mechanism to solve complex combinatorial problems in which both domain constraints and knowledge can be easily implemented.…”