Variable Neighborhood Search for Solving the Balanced Location Problem

Abstract

In this paper we propose a general variable neighborhood search approach for the balanced location problem. Next to large shaking neighborhoods, the embedded variable neighborhood descent utilizes three neighborhood structures that focus on different solution aspects. By a computational study, we show that this VNS outperforms existing methods with respect to average solution quality and stability.