Variable neighborhood search (VNS) [4, 5] is a metaheuristic for solving optimization problems based on a simple principle: systematic changes of neighborhoods within the search, both in the descent to local minima and in the escape from the valleys which contain them. VNS applications have been numerous and successful. Many extensions have been made, mainly to be able to solve large problem in...

A new hybrid algorithm is proposed in this paper. An independent task scheduling algorithm is designed based on the hybrid algorithm. The hybrid algorithm adopt list scheduling method to code harmony solution and convert harmony vector to priority-based independent task scheduling model, and perform variable neighborhood search on harmony solutions to improve Harmony Search efficiency and solut...

Flexible job-shop scheduling problem (FJSP) is an extension of the classical job-shop scheduling problem. FJSP is NP-hard and mainly presents two difficulties. The first one is to assign each operation to a machine out of a set of capable machines, and the second one deals with sequencing the assigned operations on the machines. This paper proposes a parallel variable neighborhood search (PVNS)...

This paper considers the VRP Problem with Soft Time-Windows (VRPSTW), a challenging routing problem due to its combination of hard time windows and a lexicographic objective function minimizing the number of vehicles, the violations of the soft time windows, and the total travel distance. The paper presents a multi-stage, variable neighborhood search algorithm for the VRPSTW, which uses the sam...

In this paper, we propose a Particle Swarm Optimization (PSO) based solution to the Orienteering Problem. A major problem in many PSO applications is the premature convergence of some particles to local optimums. To overcome this problem in our application, such particles are re-initiated; consequently, the exploration capability of PSO is improved. Furthermore, by employing Reduced Variable Ne...

The p-Center problem consists of locating p facilities and assigning clients to them in order to minimize the maximum distance between a client and the facility to which he or she is allocated. In this paper, we present a basic Variable Neighborhood Search and two Tabu Search heuristics for the p-Center problem without the triangle inequality. Both proposed methods use the 1-interchange (or ver...

This paper proposes a way to combine the Mesh Adaptive Direct Search (MADS) algorithm, which extends the Generalized Pattern Search (GPS) algorithm, with the Variable Neighborhood Search (VNS) metaheuristic, for nonsmooth constrained optimization. The resulting algorithm retains the convergence properties of MADS, and allows the far reaching exploration features of VNS to move away from local s...

In this study, we propose a robust variant of a dynamic facility location problem that arises from optimizing the emergency service network of Police Special Forces Units (PSFUs) in the Republic of Serbia. We present for the first time a mathematical programming formulation of the problem under consideration. We further propose a Variable Neighborhood Search (VNS) method with an efficient local...

Systematic change of neighborhood within a possibly randomized local search algorithm yields a simple and e€ective metaheuristic for combinatorial and global optimization, called variable neighborhood search (VNS). We present a basic scheme for this purpose, which can easily be implemented using any local search algorithm as a subroutine. Its e€ectiveness is illustrated by solving several class...

We analyze five parallelization strategies for the Variable Neighborhood Search (VNS) meta-heuristic. They are based on asynchronous cooperation of several search threads. We tested parallelization on various levels, from a low-level parallel neighborhood exploration, through medium-grained asynchronous execution of basic VNS steps (shaking and local search), to the coarse-grained asynchronous ...