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This is a comprehensive review of the Greedy Randomized Adaptive SearchProcedure (GRASP) metaheuristic and its hybridization with Path Relinking (PR)over the past two decades. GRASP with PR has become a widely adopted approachfor solving hard optimization problems since its proposal in 1999. The papercovers the historical development of GRASP with PR and its theoreticalfoundations, as well as recent advances in its implementation and application.The review includes a critical analysis of variants of PR, includingmemory-based and randomized designs, with a total of ten differentimplementations. It describes these advanced designs both theoretically andpractically on two well-known optimization problems, linear ordering andmax-cut. The paper also explores the hybridization of GRASP with PR and othermetaheuristics, such as Tabu Search and Scatter Search. Overall, this reviewprovides valuable insights for researchers and practitioners seeking to utilizeGRASP with PR for solving optimization problems.

20 years of Greedy Randomized Adaptive Search Procedures with Path Relinking