Variable Neighborhood Search

This book constitutes the refereed post-conference proceedings of the 6th International Conference on Variable Neighborhood Search, ICVNS 2018, held in Sithonia, Greece, in October 2018.

ICVNS 2018 received 49 submissions of which 23 full papers were carefully reviewed and selected.

VNS is a metaheuristic based on systematic changes in the neighborhood structure within a search for solving optimization problems and related tasks. The main goal of ICVNS 2018 was to provide a stimulating environment in which researchers coming from various scientific fields could share and discuss their knowledge, expertise, and ideas related to the VNS metaheuristic and its applications.

Inhalt

Improved variable neighbourhood search heuristic for quartet clustering.- On the k-medoids model for semi-supervised clustering.- Complexity and Heuristics for the Max Cut-Clique Problem.- A VNS approach to solve multi-level capacitated lotsizing problem with backlogging.- How to locate disperse obnoxious facility centers?.- Basic VNS algorithms for solving the pollution location inventory routing problem.- Less is More: The Neighborhood Guided Evolution Strategies convergence on some classic neighborhood operators.- New VNS variants for the Online Order Batching Problem.- An adaptive VNS and Skewed GVNS approaches for School Timetabling Problems.- Finding balanced bicliques in bipartite graphs using Variable Neighborhood Search.- General Variable Neighborhood Search for Scheduling Heterogeneous Vehicles in Agriculture.- Detecting weak points in networks using Variable Neighborhood Search.- A Variable neighborhood search with integer programming for the zero-one Multiple-Choice Knapsack Problem with Setup .- A VNS-based Algorithm with Adaptive Local Search for Solving the Multi-Depot Vehicle Routing Problem.- Skewed Variable Neighborhood Search Method for the Weighted Generalized Regenerator Location Problem.- Using a variable neighborhood search to solve the single processor scheduling problem with time restrictions.- An Evolutionary Variable Neighborhood Descent for addressing an electric VRP variant.- A Variable Neighborhood Descent heuristic for the multi-quay Berth Allocation and Crane Assignment Problem under availability constraints.- A Variable Neighborhood Search approach for solving the Multidimensional Multi-way Number Partitioning Problem.- A general variable neighborhood search with Mixed VND for the multi-Vehicle multi-Covering Tour Problem.- A Hybrid Firefly - VNS Algorithm for the Permutation Flowshop Scheduling Problem.- Studying the impact of perturbation methods on the efficiency of GVNS for the ATSP.- A general variable neighborhood search algorithm to solve vehicle routing problems with optional visits.