Fundamentals of Scatter Search and Path Relinking

By Fred Glover, Manuel Laguna, Rafael Martí. 2000

871 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/49b5d3ac6034380938087389a823186eadeae794

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Citations in the corpus

A Hybrid Heuristic for the p-Median Problem (2004, methodology): “Originally proposed for tabu search and scatter search [13, 14], this procedure was first applied within the GRASP framework by Laguna and Mart́ı [22], and widely applied ever since (Resende and Ribeiro [30] present numerous examples).”
A Survey of Multiobjective Evolutionary Algorithms Based on Decomposition (2017, methodology): “[110] and path-relinking [111] as the discrete reproduction operators within the MOEA/D framework for solving MOKPs.”
Greedy Randomized Adaptive Search Procedures. (2003, methodology): “This technique was originally proposed by Glover [86] as an intensification strategy to explore trajectories connecting elite solutions obtained by tabu search or scatter search [87, 88, 89].”
Metaheuristics in combinatorial optimization: Overview and conceptual comparison (2003, background): “Scatter Search and its generalized form called Path Relinking [Glover 1999; Glover et al. 2000] differ from EC algorithms mainly by providing unifying principles for joining (or recombining) solutions based on generalized path constructions in Euclidean or neighborhood spaces.”
Metaheuristics in Combinatorial Optimization (2005, methodology): “A precise description of this metaheuristic may be found in Glover, Laguna, and Marti (2000) , and Laguna (2002).”
Exploring relaxation induced neighborhoods to improve MIP solutions (2005, background): “, genetic algorithms [28], scatter search, and path relinking [19]), are known to provide excellent feasible solutions quite quickly for many problems.”
AbYSS: Adapting Scatter Search to Multiobjective Optimization (2008, background): “Scatter search has been found to be successful in a wide variety of optimization problems [8], but until recently it had not been extended to deal with MOPs.”
The p-median problem: A survey of metaheuristic approaches (2005, unknown): “jack.brimberg@rmc.ca”
Experimental investigation of heuristics for resource-constrained project scheduling: An update (2006, background): “[22]), a population based framework which can be viewed as a variant of genetic algorithms.”
Simulation optimization: a review of algorithms and applications (2014, methodology): “Similar to Tabu search, Scatter Search also utilize adaptive memory in storing best solutions (Glover and Laguna 2000; Martí et al. 2006).”
A bi-objective reverse logistics network analysis for post-sale service (2008, methodology): “The template for implementing SS consists of five component methods [29]: (1) A diversification generation method to generate P(P Size) diverse trial solutions.”
Memetic algorithms and memetic computing optimization: A literature review (2012, background): “The latter are common in scatter search [62] (SS), an optimization paradigm closely related to memetic algorithms in which the population (or reference set in the SS jargon) is divided in tiers: entrance to them is gained by solution on the basis of fitness in one case, or diversity in the other cas”
Scatter Search: Diseño Básico y Estrategias avanzadas (2002, background): “Glover, Laguna y Martí [8] estudian las implementaciones más recientes del método en la resolución de problemas de optimización combinatoria.”
Parameter estimation in large-scale systems biology models: a parallel and self-adaptive cooperative strategy (2017, background): “Scatter search (SS) [55] is a population based metaheuristic for global optimization that constructs new solutions based on systematic combinations of the members of a reference set (called RefSet in this context).”
Efficiently Solving the Redundancy Allocation Problem Using Tabu Search (2003, background): “The results demonstrate the benefits of tabu search for solving this type of problem.”