Abstract. This paper describes variants of GRASP (greedy randomized adaptive search procedure) with path relinking for the three index assignment problem (AP3). GRASP is a multi-start metaheuristic for combinatorial optimization. It usually consists of a construction procedure based on a greedy randomized algorithm and of a local search. Path relinking is an intensification strategy that explor...

This paper describes a GRASP with path-relinking heuristic for the quadratic assignment problem. GRASP is a multi-start procedure, where different points in the search space are probed with local search for high-quality solutions. Each iteration of GRASP consists of the construction of a randomized greedy solution, followed by local search, starting from the constructed solution. Path-relinking...

This paper proposes a learning-based path relinking algorithm (LPR) for solving the bandwidth coloring problem and the bandwidth multicoloring problem. Based on the population path-relinking framework, the proposed algorithm integrates a learning-driven tabu optimization procedure and a path-relinking operator. LPR is assessed on two sets of 66 common benchmark instances, and achieves highly co...

The evolutionary approach called Scatter Search, and its generalized form called Path Relinking, have proved unusually effective for solving a diverse array of optimization problems from both classical and real world settings. Scatter Search and Path Relinking differ from other evolutionary procedures, such as genetic algorithms, by providing unifying principles for joining solutions based on g...

In this chapter, a path relinking method for the maximum cut problem is investigated. The authors consider an implementation of the path-relinking, where it is utilized as a subroutine for another meta-heuristic search procedure. Particularly, the authors focus on the global equilibrium search method to provide a set of high quality solutions, the set that is used within the path relinking meth...

The exploration of hybrid metaheuristics — combination of metaheuristics with concepts and processes from other research areas — has been an important trend in combinatorial optimization research. In this work, we developed a hybrid version of the GRASP metaheuristic which incorporates the path-relinking procedure — a memory-based intensification strategy — and a data mining module. Computation...

1 Path relinking for the vehicle routing problem Path relinking is a relatively new metaheuristic technique for combinatorial optimization, proposed by Glover (see e.g. [3]). Path relinking attempts to find new good solutions by examining the solutions that are on a path from an initial (incumbent) to a final (guiding) solution. By definition, each move on the path makes the solution more diffe...

We propose several new hybrid heuristics for the differential dispersion problem, 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 pairs of eli...

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...

The paper presents Greedy Randomized Adaptive Search Procedure with Path Relinking (GRASP with PR) for the Critical Node Detection Problem (CNDP). An evolutionary Path Relinking mechanism is added to GRASP with PR to intensify. Our computational experiments show that this algorithm is a competitive method compared with the previously proposed methods for solving CNDP such as Variable Neighborho...