Christian Blum
- R.L. Stewart and R.A. Russell. A Distributed Feedback Mechanism to Regulate Wall Construction by a Robotic Swarm. Adaptive Behavior, Vol. 14, No. 1, 21-51 (2006). Google Scholar
Digital Library
- A. Grushin and J.A. Reggia. Stigmergic self-assembly of prespecified artificial structures in a constrained and continuous environment. Journal Integrated Computer-Aided Engineering, Vol. 13, No. 4, 289-312 (2006).Google ScholarDigital Library
- E. Bonabeau, S. Guerin, D. Snyers, P. Kuntz and G. Theraulaz. Three-dimensional architectures grown by simple 'stigmergic' agents. Biosystems, Vol. 56, No. 1, 13-32 (2000).Google ScholarCross Ref
- M. Reimann. Guiding ACO by Problem Relaxation: A Case Study on the Symmetric TSP, In: Proceedings of HM 2007, volume 4771, Springer LNCS, pages 45-56, 2007. Google ScholarDigital Library
- R. K. Ahuja, O. Ergun, J. B. Orlin, and A. P. Punnen. A survey of very large-scale neighborhood search techniques, Discrete Applied Mathematics, 123(1-3):75-102, 2002. Google ScholarDigital Library
- M. Chiarandini, I. Dumitrescu, and T. Stützle. Very Large-Scale Neighborhood Search: Overview and Case Studies on Coloring Problems, In: Hybrid Metaheuristics-An Emerging Approach to Optimization, volume 114 of Studies in Computational Intelligence, pages 117-150, Springer Verlag, Berlin, Germany, 2008.Google Scholar
- C. Blum and M. J. Blesa. Combining ant colony optimization with dynamic programming for solving the k-cardinality tree problem, In: Proceedings of IWANN 2005, volume 3512 of Springer LNCS, pages 25-33, 2005. Google ScholarDigital Library
- C. Walshaw. Multilevel refinement for combinatorial optimisation, Annals of Operations Research, 131:325-372, 2004.Google ScholarCross Ref
- C. Walshaw. Multilevel refinement for combinatorial optimisation: boosting metaheuristic performance, In: Hybrid Metaheuristics-An Emerging Approach to Optimization, volume 114 of Studies in Computational Intelligence, pages 261-289, Springer Verlag, Berlin, Germany, 2008.Google Scholar
- P. Korosec, J. Silc, and B. Robic. Solving the mesh-partitioning problem with an ant-colony algorithm, Parallel Computing, 30(5-6):785-801, 2004. Google ScholarDigital Library
- M. Leng and S. Yu. An Effective Multi-level Algorithm Based on Ant Colony Optimization for Bisecting Graphs, In: Proceedings of PAKDD 2007, volume 4426 of Spriner LNAI, pages 138-149, 2007. Google ScholarDigital Library
- C. Blum, M. Yabar, and M. J. Blesa. An ant colony optimization algorithm for DNA sequencing by hybridization, Computers & Operations Research, 35:3620-3635, 2008. Google ScholarDigital Library
- V. Maniezzo. Exact and approximate nondeterministic tree-search procedures for the quadratic assignment problem, INFORMS Journal on Computing, 11(4):358-369, 1999.Google ScholarCross Ref
- V. Maniezzo and A. Carbonaro. An ANTS heuristic for the frequency assignment problem, Future Generation Computer Systems, 16:927-935, 2000. Google ScholarDigital Library
- C. Blum. Beam-ACO-hybridizing ant colony optimization with beam search: an application to open shop scheduling, Computers and Operations Research, 32:1565-1591, 2005. Google ScholarDigital Library
- J. Caldeira, R. Azevedo, C. A. Silva, and J. M. C. Sousa. Beam-ACO Distributed Optimization Applied to Supply-Chain Management, In: Proceedings of IFSA 2007, volume 4529 of Springer LNCS, pages 799-809, 2007. Google ScholarDigital Library
- J. Caldeira, R. Azevedo, C. A. Silva, and J. M. C. Sousa. Supply-Chain Management Using ACO and Beam-ACO Algorithms, In: Proceedings of FUZZ-IEEE 2007, pages 1-6, IEEE press, 2007.Google ScholarCross Ref
- C. Blum. Beam-ACO for simple assembly line balancing, INFORMS Journal on Computing, 2008. In press.Google ScholarCross Ref
- B. Meyer and A. Ernst. Integrating ACO and Constraint Propagation, In: Proceedings of ANTS 2004, volume 3172 of Springer LNCS, pages 166-177, 2004.Google ScholarCross Ref
- M. Khichane, P. Albert, and C. Solnon. CP with ACO, In: Proceedings of CPAIOR 2008, volume 5015 of Springer LNCS, pages 328-332, 2008. Google ScholarDigital Library
Index Terms
- Ant colony optimization
Recommendations
Ant colony optimization theory: a survey
Research on a new metaheuristic for optimization is often initially focused on proof-of-concept applications. It is only after experimental work has shown the practical interest of the method that researchers try to deepen their understanding of the ...
Extended trail reinforcement strategies for ant colony optimization
SEMCCO'11: Proceedings of the Second international conference on Swarm, Evolutionary, and Memetic Computing - Volume Part IAnt colony optimization (ACO) is a metaheuristic inspired by the foraging behavior of biological ants that was successfully applied for solving computationally hard problems. The fundamental idea that drives the ACO is the usage of pheromone trails for ...
Particle swarm optimizer, ant colony strategy and harmony search scheme hybridized for optimization of truss structures
A heuristic particle swarm ant colony optimization (HPSACO) is presented for optimum design of trusses. The algorithm is based on the particle swarm optimizer with passive congregation (PSOPC), ant colony optimization and harmony search scheme. HPSACO ...
Comments