Image
volume 3 issue 11

APPLYING MULTI- LEVEL ANTCOLONY OPTIMIZATION TO RESTRICTED FOREST

Abstract

Since the beginning of the last century, one of the most important concerns has been the problems arising from the planning of forest transport. Off-road activities are those that involve the transportation of wood from stump locations to roadside landings or landings in centralized locations. The term "on-road activities" refers to the process of transporting timber to its final destinations using land-based vehicles. The exact algorithm and approximation algorithm, both are different methods that have been used in the process of solving ftpp.  The core of approximation algorithms commonly referred to as heuristics is the process of ranking a large number of possible answers and choosing the most appropriate one. The fact that exact algorithms can generate optimal answers is the most important advantage associated with using them.

Keywords
  • Multi- Level,
  • Ant colony.
References
  • Ajith Abraham and Lakhmi Jain. Evolutionary Multi-objective Optimization. Springer, 2005.
  • Jesu´s S´aez Aguado. Fixed charge transportation problems: a new heuristic ap- proach based on lagrangean relaxation and the solving of core problems. Annals of Operations Research, 172(1):45–69, 2009.
  • Daniel Angus and Clinton Woodward. Multiple objective ant colony optimisa- tion. Swarm Intelligence, 3(1):69–85, 2009.
  • Ronald G Askin, Steven H Cresswell, Jeffrey B Goldberg, and Asoo J Vakharia. A hamiltonian path approach to reordering the part-machine matrix for cellular manufacturing. International Journal of Production Research, 29(6):1081–1100, 1991.
  • Prasanna Balaprakash, Mauro Birattari, and Thomas Stu¨tzle. Improvement strategies for the f-race algorithm: Sampling design and iterative refinement. In Hybrid Metaheuristics, pages 108–122. Springer, 2007.
  • Ali Berrichi, Farouk Yalaoui, Lionel Amodeo, and M Mezghiche. Bi-objective ant colony optimization approach to optimize production and maintenance schedul- ing. Computers & Operations Research, 37(9):1584–1596, 2010.
  • Leonora Bianchi, Marco Dorigo, Luca Maria Gambardella, and Walter J Gutjahr. A survey on metaheuristics for stochastic combinatorial optimization. Natural Computing: An International Journal, 8(2):239–287, 2009.
  • Leonora Bianchi, Luca Maria Gambardella, and Marco Dorigo. An ant colony op- timization approach to the probabilistic traveling salesman problem. In Parallel Problem Solving from Nature PPSN VII, pages 883–892. Springer, 2002.
  • Mauro Birattari, Thomas Stu¨tzle, Luis Paquete, Klaus Varrentrapp, et al. A racing algorithm for configuring metaheuristics. In GECCO, volume 2, pages 11–18. Citeseer, 2002.
  • Mauro Birattari, Zhi Yuan, Prasanna Balaprakash, and Thomas Sttzle. F-race and iterated f-race: An overview. In Thomas Bartz-Beielstein, Marco Chiaran- dini, Lus Paquete, and Mike Preuss, editors, Experimental Methods for the Analy- sis of Optimization Algorithms, pages 311–336. Springer Berlin Heidelberg, 2010.
  • Norbert Blum. A New Approach To Maximum Matching In General Graphs. Springer, 1990.
  • Eric Bonabeau and Christopher Meyer. Swarm intelligence: A whole new way to think about business. Harvard Business Review, 79(5):106–115, 2001.
  • Juergen Branke and Jawad Asem Elomari. Meta-optimization for parameter tuning with a flexible computing budget. In Proceedings of The Fourteenth In- ternational Conference on Genetic and Evolutionary Computation Conference, pages 1245–1252. ACM, 2012.
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Prashant Kumar. (2020). APPLYING MULTI- LEVEL ANTCOLONY OPTIMIZATION TO RESTRICTED FOREST. International Journal of Multidisciplinary Research and Studies, 3(11), 01–13. Retrieved from https://ijmras.com/index.php/ijmras/article/view/180

Download Citation

Downloads

Download data is not yet available.

Similar Articles

You may also start an advanced similarity search for this article.