We suggest a new heuristic for solving unconstrained continuous optimization problems. It is based on a generalized version of the variable neighborhood search metaheuristic. Different neighborhoods and distributions, induced from different metrics are ranked and used to get random points in the shaking step. We also propose VNS for solving constrained optimization problems. The constraints are...

This paper is concerned with the development of intelligent decision support methodologies for nurse rostering problems in large modern hospital environments. We present an approach which hybridises heuristic ordering with variable neighbourhood search. We show that the search can be extended and the solution quality can be significantly improved by the careful combination and repeated use of h...

This work addresses the Vehicle Routing Problem with Simultaneous Pickup and Delivery (VRPSPD). Due to its complexity, we propose a heuristic algorithm for solving it, so-called GENVNS-TS-CL-PR. This algorithm combines the heuristic procedures Cheapest Insertion, Cheapest Insertion with multiple routes, GENIUS, Variable Neighborhood Search (VNS), Variable Neighborhood Descent (VND), Tabu Search...

1 This paper addresses a real-world customer segmentation problem from a beverage distribution 2 firm. The firm wants to partition a set of customers, who share geographical and marketing attributes, 3 into segments according to certain requirements: (a) customers allocated to the same segment must 4 have very similar attributes: type of contract, type of store and the average difference of pur...

Finding communities, or clusters, in networks, or graphs, has been the subject of intense studies in the last ten years. The most used criterion for that purpose, despite some recent criticism, is modularity maximization, proposed by Newman and Girvan. It consists in maximizing the sum for all clusters of the number of inner edges minus the expected number of inner edges assuming the same distr...

Efficient constructive heuristics have been designed for most of the difficult combinatorial optimisation problems. Performance of these heuristics may vary from one instance to another and hence it is beneficial to be able to select an instance of the heuristic which is best suited to a given instance of the problem. Both of the heuristic search algorithm and hyper-heuristic approaches try to ...

We propose several new hybrid heuristics for the differential dispersion problem are proposed, the best of which consists of a GRASP with sampled greedy construction with variable neighborhood search for local improvement. The heuristic maintains an elite set of high-quality solutions throughout the search. After a fixed number of GRASP iterations, exterior path relinking is applied between all...

We present a data mining approach for reducing the search space of local search algorithms in large-scale set partitioning problems (SPPs). We construct a k-nearest neighbor graph by extracting variable associations from the instance to be solved, in order to identify promising pairs of flipping variables in the large neighborhood search. We incorporate the search space reduction technique into...

Scheduling problems play a big role in manufacturing and planning the production for increasing the production efficiency and assigning the resources to operations. Furthermore, in many manufacturing systems there is a physical space between stages that called intermediate buffers. In this study, a model is proposed for minimizing the makespan of a hybrid flow shop scheduling problem with inter...

The rapid evolution of real-time multimedia applications requires Quality of Service (QoS) based multicast routing in underlying computer networks. The constrained Steiner Tree, as the underpinning mathematical structure, is a well-known NP-complete problem. In this paper we investigate a variable neighborhood descent (VND) search, a variant of variable neighborhood search, for the delay-constr...