Variable Neighborhood Search (VNS) is a metaheuristic for solving optimization problems based on a systematic change of neighborhoods. In recent years, a large variety of VNS strategies have been proposed. However, we have only found limited experimental comparisons among different VNS variants. This paper reviews three VNS strategies for finding near-optimal solutions for vertex-cut minimizati...

A variable neighborhood search approach to the exploration of an online social network Vera Kovačević Vujčić, Mirjana Čangalović and Jozef Kratica Using VNS for the optimal synthesis of the communication tree in wireless sensor networks Adil Erzin, Roman V. Plotnikov

To solve problems with Local Search procedures, neighborhoods have to be defined. During the resolution, a solution is typically replaced by the best solution found in its neighborhood. A question concerns the size of the neighborhood. If a small neighborhood can be explored in polynomial time, a large neighborhood search may bring a faster convergence to a local optimum of good quality (see [1...

We present a variable neighborhood search (VNS) for the 3-staged 2-dimensional cutting stock problem employing “ruin-and-recreate”-based very large neighborhood search in which parts of the incumbent solution are destroyed and rebuilt using construction heuristics and dynamic programming. Experimental results show that for instances where the sizes of the elements are not too small compared to ...

Land-use allocation is of great significance in urban development. This type of allocation is usually considered to be a complex multi-objective spatial optimization problem, whose optimized result is a set of Pareto-optimal solutions (Pareto front) reflecting different tradeoffs in several objectives. However, obtaining a Pareto front is a challenging task, and the Pareto front obtained by sta...

The AutoGraphiX 2 system is used to compare the index of a connected graph G with a number of other graph theoretical invariants, i.e., chromatic number, maximum, minimum and average degree, diameter, radius, average distance, independence and domination numbers. In each case, best possible lower and upper bounds, in terms of the order of G, are sought for sums, differences, ratios and products...

A set of vertices S in a graph G is a clique if any two of its vertices are adjacent. The clique number ω is the maximum cardinality of a clique in G. A series of best possible lower and upper bounds on the difference, sum, ratio or product of ω and some other common invariants of G were obtained by the system AGX 2, and most of them proved either automatically or by hand. In the present paper,...

The resource constrained multi-mode multi-project scheduling problem (RCMMMPSP) is a notoriously difficult combinatorial optimization problem. For a given set of activities, feasible execution mode assignments and execution starting times must be found such that some optimization function, e. g. the makespan, is optimized. When determining an optimal (or at least feasible) assignment of decisio...

Local genetic algorithms have been designed with the aim of providing effective intensification. One of their most outstanding features is that they may help classical local search-based metaheuristics to improve their behavior. This paper focuses on experimentally investigating the role of a recent approach, the binary-coded local genetic algorithm (BLGA), as context-independent local search o...

We propose new local search algorithms for minimum makespan machine scheduling problems, which perform multiple exchanges of jobs among machines. Inspired by the work of Thompson and Orlin (1989) on cyclic transfer neighborhood structures, we model multiple exchanges of jobs as special disjoint cycles and paths in a suitably defined improvement graph, by extending definitions and properties int...