Operators of public bicycle sharing systems (BSSs) have to regularly redistribute bikes across their stations in order to avoid them getting overly full or empty. We consider the dynamic case where this is done while the system is in use. There are two main objectives: On the one hand it is desirable to reach particular target fill levels at the end of the process so that the stations are likel...

Chemical graphs, as other ones, are regular if all their vertices have the same degree. Otherwise, they are irregular, and it is of interest to measure their irregularity both for descriptive purposes and for QSAR/QSPR studies. Three indices have been proposed in the literature for that purpose: those of Collatz-Sinogowitz, of Albertson, and of Bell's variance of degrees. We study their propert...

In this paper, we study various parallelization schemes for the Variable Neighborhood Search (VNS) metaheuristic on a CPU-GPU system via OpenMP and OpenACC. A hybrid parallel VNS method is applied to recent benchmark problem instances for the multi-product dynamic lot sizing problem with product returns and recovery, which appears in reverse logistics and is known to be NP-hard. We report our f...

The Variable Neighborhood Search (VNS) metaheuristic is based on systematic changes in the neighborhood structure within a search, and has been succesfully applied for solving various discrete, global optimization problems, and related tasks. This Call for Papers addresses the recently growing interest of the research community working on the VNS methodology. This special issue of the Internati...

We consider a real-world problem arising in a warehouse for spare parts. Items ordered by customers shall be collected and for this purpose our task is to determine efficient pickup tours within the warehouse. The algorithm we propose embeds a dynamic programming algorithm for computing individual optimal walks through the warehouse in a general variable neighborhood search (VNS) scheme. To enh...

This work deals with the application of a variable neighborhood search (VNS) to the capacitated location-routing problem (LRP) as well as to the more general periodic LRP (PLRP). For this, previous successful VNS algorithms for related problems are considered and accordingly adapted as well as extended. The VNS is subsequently combined with three very large neighborhood searches (VLNS) based on...

This paper presents a new hybridization of VNS and path-relinking on a particle swarm framework for the permutational fowshop scheduling problem with total flowtime criterion. The operators of the proposed particle swarm are based on path-relinking and variable neighborhood search methods. The performance of the new approach was tested on the bechmark suit of Taillard, and five novel solutions ...

A hybridisation of a clustering-based technique and of a Variable Neighbourhood Search (VNS) is designed to solve large-scale p-median problems. The approach is based on a multi-stage methodology where learning from previous stages is taken into account when tackling the next stage. Each stage is made up of several subproblems that are solved by a fast procedure to produce good feasible solutio...

This paper presents a Variable Neighborhood Search (VNS) algorithm for the container loading problem. The algorithm combines a constructive procedure based on the concept of maximal-space, with five new movements defined directly on the physical layout of the packed boxes, which involve insertion and deletion strategies. The new algorithm is tested on the complete set of Bischoff and Ratcliff p...

An important type of methods for learning belief networks from data are those based on the use of a scoring metric, to evaluate the fitness of any given candidate network to the data base, and a search procedure to explore the set of candidate networks. In this paper we propose a new method that carries out the search not in the space of directed acyclic graphs but in the space of the orderings...