A multiple-level variable neighborhood search approach to the orienteering problem

References

• Avanthay , C. , Hertz , A. and Zufferey , N. 2003 . A variable neighborhood search for graph coloring . European Journal of Operational Research , 151 : 379 – 388 .
   Web of Science ®Google Scholar
• Bräysy , O. 2003 . A reactive variable neighborhood search for the vehicle routing problem with time windows . INFORMS Journal on Computing , 153 : 47 – 368 .
   Google Scholar
• Carrabs , F. , Cordeau , J.-F. and Laporte , G. 2007 . Variable neighborhood search for the pickup and delivery traveling salesman problem with LIFO loading . INFORMS Journal on Computing , 19 : 618 – 632 .
   Web of Science ®Google Scholar
• Chao , I.-M. , Golden , B. L. and Wasil , E. A. 1996 . A fast and effective heuristic for the orienteering problem . European Journal of Operational Research , 88 : 475 – 489 .
   Web of Science ®Google Scholar
• Del Pia , A. and Filippi , C. 2006 . A variable neighborhood descent algorithm for a real waste collection problem with mobile depots . International Transactions in Operational Research , 13 : 125 – 141 .
   Google Scholar
• Fleszar , K. and Hindi , K. S. 2004 . Solving the resource-constrained project scheduling problem by a variable neighborhood search . European Journal of Operational Research , 155 : 402 – 413 .
   Web of Science ®Google Scholar
• García-López , F. , Melián-Batista , B. , Moreno-Pérez , J. A. and Moreno-Vega , J. M. 2002 . The parallel variable neighborhood search for the p-Median problem . Journal of Heuristics , 8 : 375 – 388 .
   Google Scholar
• Golden , B. L. , Levy , L. and Vohra , R. 1987 . The orienteering problem . Naval Research Logistics , 34 : 307 – 318 .
   Web of Science ®Google Scholar
• Golden , B. L. , Wang , Q. and Liu , L. 1988 . A multifaceted heuristic for the orienteering problem . Naval Research Logistics , 35 : 359 – 366 .
   Web of Science ®Google Scholar
• Hansen , P. and Mladenović , N. 2001 . Variable neighborhood search: Principles and applications . European Journal of Operational Research , 130 : 449 – 467 .
   Web of Science ®Google Scholar
• Hansen , P. , Mladenović , N. and Pérez , J. A. M. 2010 . Variable neighborhood search: Methods and applications . Annals of Operations Research , 175 : 367 – 407 .
   Web of Science ®Google Scholar
• Hansen , P. , Oğuz , C. and Mladenović , N. 2008 . Variable neighborhood search for minimum cost berth allocation . European Journal of Operational Research , 191 : 636 – 649 .
   Web of Science ®Google Scholar
• Jaén , J. , Mocholí , J. A. , Catalá , A. and Navarro , E. 2011 . Digital ants as the best cicerones for museum visitors . Applied Soft Computing , 11 : 111 – 119 .
   Google Scholar
• Ke, L. and Z. Feng, “A new ant colony optimization approach for the orienteering problem,” Proceedings of the 7th World Congress on Intelligent Control and Automation, Chongqing, China, 2027–2032 (2008).
   Google Scholar
• Keller , P. 1989 . Algorithms to solve the orienteering problem: A comparison . European Journal of Operational Research , 41 : 224 – 231 .
   Web of Science ®Google Scholar
• Kulturel-Konak , S. , Norman , B. A. , Coit , D. W. and Smith , A. E. 2004 . Exploiting tabu-search memory in constrained problems . INFORMS Journal on Computing , 16 : 241 – 254 .
   Web of Science ®Google Scholar
• Liang , Y. C. and Chen , Y. C. 2007 . Redundancy allocation of series-parallel systems using a variable neighborhood search algorithm . Reliability Engineering and System Safety , 92 : 323 – 331 .
   Web of Science ®Google Scholar
• Liang , Y. C. and Lo , M. H. 2010 . Multi-objective redundancy allocation optimization using a variable neighborhood search algorithm . Journal of Heuristics , 16 : 511 – 535 .
   Web of Science ®Google Scholar
• Liang , Y. C. and Lo , M. H. 2012 . A variable neighborhood search algorithm with novel archive update strategies for redundancy allocation problems . Engineering Optimization , 44 : 289 – 303 .
   Web of Science ®Google Scholar
• Liang , Y. C. , Lo , M. H. and Chen , Y. C. 2007 . Variable neighborhood search for redundancy allocation problems . IMA Journal of Management Mathematics , 18 : 135 – 156 .
   Google Scholar
• Liang , Y. C. and Smith , A. E. 2006 . An ant colony approach to the orienteering problem . Journal of the Chinese Institute of Industrial Engineers , 23 : 403 – 414 .
   Google Scholar
• Liao , C. J. and Cheng , C. C. 2007 . A variable neighborhood search for minimizing single machine weighted earliness and tardiness with common due date . Computers and Industrial Engineering , 52 : 404 – 413 .
   Web of Science ®Google Scholar
• Lusa , A. and Potts , C. N. 2008 . A variable neighborhood search algorithm for the constrained task allocation problem . Journal of the Operational Research Society , 59 : 812 – 822 .
   Web of Science ®Google Scholar
• Mladenović, N., “A variable neighborhood algorithm – A new metaheuristic for combinatorial optimization”, Abstracts of papers presented at Optimization Days, Montreal, Canada, 112 (1995).
   Google Scholar
• Mladenović , N. and Hansen , P. 1997 . Variable neighborhood search . Computers and Operations Research , 24 : 1097 – 1100 .
   Web of Science ®Google Scholar
• Ramesh , R. and Brown , K. M. 1991 . An efficient four-phase heuristic for the generalized orienteering problem . Computers and Operations Research , 18 : 151 – 165 .
   Web of Science ®Google Scholar
• Ramirez-Marquez , J. E. , Kulturel-Konak , S. and Sanseverino , C. M. R. 2010 . Probabilistic solution discovery algorithm for the orienteering problem . International Journal of Industrial and Systems Engineering , 6 : 45 – 61 .
   Google Scholar
• Ribeiro , C. C. and Souza , M. C. 2002 . Variable neighborhood search for the degree-constrained minimum spanning tree problem . Discrete Applied Mathematics , 118 : 43 – 54 .
   Web of Science ®Google Scholar
• Schilde , M. , Doerner , K. F. , Hartl , R. F. and Kiechle , G. 2009 . Metaheuristics for the bi-objective orienteering problem . Swarm Intelligence , 3 : 179 – 201 .
   Google Scholar
• Sevkli, Z. and F. E. Sevilgen, “Variable Neighborhood Search for the Orienteering Problem.” Springer, Berlin/Heidelberg, Lecture Notes in Computer Science (LNCS), 4263, 134–143 (2006).
   Google Scholar
• Souffriau , W. , Vansteenwegen , P. , Van den Berghe , G. and Van Oudheusden , D. 2008 . Automated parameterisation of a metaheuristic for the orienteering problem, adaptive and multilevel metaheuristics . Springer Series: Studies in Computational Intelligence , 136 : 255 – 269 .
   Google Scholar
• Stützle , T. and Hoos , H. H. 2000 . MAX-MIN ant system . Future Generation Computer Systems , 16 : 889 – 914 .
   Web of Science ®Google Scholar
• Tasgetiren, M. F. and A. E. Smith, “A genetic algorithm for the orienteering problem.” Proceedings of the 2000 Congress on Evolutionary Computation, La Jolla, CA 910–915 (2000).
   Google Scholar
• Tsiligirides , T. 1984 . Heuristic methods applied to orienteering . Journal of Operational Research Society , 35 : 797 – 809 .
   Web of Science ®Google Scholar
• Vansteenwegen , P. , Souffriau , W. and Van Oudheusden , D. 2011 . The orienteering problem: A survey . European Journal of Operational Research , 209 : 1 – 10 .
   Web of Science ®Google Scholar
• Wren , A. and Holliday , A. 1972 . Computer scheduling of vehicles for one or more depots to a number of delivery points . Operations Research Quarterly , 23 : 333 – 344 .
   Google Scholar