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A Hyper-Heuristic Using GRASP with Path-Relinking: A Case Study of the Nurse Rostering Problem
Abstract
The goal of hyper-heuristics is to design and choose heuristics to solve complex problems. The primary motivation behind the hyper-heuristics is to generalize the solving ability of the heuristics. In this paper, the authors propose a Hyper-heuristic using GRASP with Path-Relinking (HyGrasPr). HyGrasPr generates heuristic sequences to produce solutions within an iterative procedure. The procedure of HyGrasPr consists of three phases, namely the construction phase, the local search phase, and the path-relinking phase. To show the performance of the HyGrasPr, the authors use the nurse rostering problem as a case study. The authors use an existing simulated annealing based hyper-heuristic as a baseline. The experimental results indicate that HyGrasPr can achieve better solutions than SAHH within the same running time and the path-relinking phase is effective for the framework of HyGrasPr.
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