A Generic Bet-and-Run Strategy for Speeding Up Stochastic Local Search

A common strategy for improving optimization algorithms is to restart the algorithm when it is believed to be trapped in an inferior part of the search space. However, while specific restart strategies have been developed for specific problems (and specific algorithms), restarts are typically not regarded as a general tool to speed up an optimization algorithm. In fact, many optimization algorithms do not employ restarts at

[1]  Shaowei Cai,et al.  Balance between Complexity and Quality: Local Search for Minimum Vertex Cover in Massive Graphs , 2015, IJCAI.

[2]  Armin Biere.  Adaptive Restart Strategies for Conflict Driven SAT Solvers , 2008, SAT.

[3]  Gerhard Reinelt,et al.  TSPLIB - A Traveling Salesman Problem Library , 1991, INFORMS J. Comput..

[4]  Serdar Kadioglu,et al.  Parallel Restarted Search , 2014, AAAI.

[5]  Forschungsinstitut für Diskrete.  Chained Lin-Kernighan for Large Traveling Salesman Problems , 2003 .

[6]  David Zuckerman,et al.  Optimal speedup of Las Vegas algorithms , 1993, [1993] The 2nd Israel Symposium on Theory and Computing Systems.

[7]  Jinbo Huang,et al.  The Effect of Restarts on the Efficiency of Clause Learning , 2007, IJCAI.

[8]  Olivier Teytaud,et al.  A Rigorous Runtime Analysis for Quasi-Random Restarts and Decreasing Stepsize , 2011, Artificial Evolution.

[9]  Juliane Jung,et al.  The Traveling Salesman Problem: A Computational Study , 2007 .

[10]  T. Stützle,et al.  Iterated Local Search: Framework and Applications , 2018, Handbook of Metaheuristics.

[11]  Eduardo Lalla-Ruiz,et al.  Improving solver performance through redundancy , 2016 .

[12]  Matteo Fischetti,et al.  Exploiting Erraticism in Search , 2014, Oper. Res..

[13]  Ryan A. Rossi,et al.  The Network Data Repository with Interactive Graph Analytics and Visualization , 2015, AAAI.

[14]  Gilles Audemard,et al.  Refining Restarts Strategies for SAT and UNSAT , 2012, CP.

[15]  Panos M. Pardalos,et al.  Experimental Analysis of Approximation Algorithms for the Vertex Cover and Set Covering Problems , 2006, Comput. Oper. Res..

[16]  Abdul Sattar,et al.  NuMVC: An Efficient Local Search Algorithm for Minimum Vertex Cover , 2014, J. Artif. Intell. Res..

[17]  Richard F. Hartl,et al.  Scheduling periodic customer visits for a traveling salesperson , 2007, Eur. J. Oper. Res..

[18]  Faisal N. Abu-Khzam,et al.  Scalable Parallel Algorithms for FPT Problems , 2006, Algorithmica.

[19]  Benjamin Doerr,et al.  Money for Nothing: Speeding Up Evolutionary Algorithms Through Better Initialization , 2015, GECCO.

[20]  Rafael Martí.  Multi-Start Methods , 2003, Handbook of Metaheuristics.