Performance evaluation of an adaptive ant colony optimization applied to single machine scheduling

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5361 LNAI, Issue , 2008, Pages 411-420

  Anghinolfi, Davide ^a   Boccalatte, Antonio ^a   Paolucci, Massimo ^a   Vecchiola, Christian ^b  

^a UNIVERSITY OF GENOA   (Italy)

^b UNIVERSITY OF MELBOURNE   (Australia)

Author keywords

Ant colony optimization; Metaheuristics; Scheduling

Indexed keywords

BENCHMARKING; MACHINERY; MATHEMATICAL MODELS; SCHEDULING; SCHEDULING ALGORITHMS;

ACO ALGORITHMS; ADAPTATION MECHANISMS; ANT COLONY OPTIMIZATION; EXPERIMENTAL CAMPAIGNS; METAHEURISTIC ALGORITHMS; METAHEURISTICS; PARAMETER ADAPTATIONS; PERFORMANCE EVALUATIONS; PHEROMONE MODELS; PRELIMINARY PARAMETERS; SELF-ADAPTIVE; SETUP TIMES; SINGLE MACHINE SCHEDULING; SINGLE MACHINES; TOTAL WEIGHTED TARDINESSES;

OPTIMIZATION;

EID: 58349119006     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-89694-4_42     Document Type: Conference Paper

References (17)

1. Dorigo, M., Stützle, T.: Ant Colony Optimization. MIT Press, Cambridge (2004)
2. Dorigo, M.: Optimization, learning and natural algorithms (in Italian). PhD Thesis, Dipartimento di Electronica, Politecnico di Milano, Italy (1992)
3. Sutton, R.S., Barto, A.G.: Reinforcement Learning: An Introduction. MIT Press, Cambridge (1998)
4. Kennedy, J., Eberhart, R.C.: Swarm Intelligence. Morgan Kaufmann Publishers, San Francisco (2001)
5. Stützle, T., Hoos, H.H.: Max-min ant system. Future Generation Computer System 16, 889-914 (2000)
6. Anghinolfi, D., Paolucci, M.: A new ant colony optimization approach for the single machine total weighted tardiness scheduling problem. International Journal of Operations Research 5(1), 1-17 (2008)
7. Cicirello, V.A.: Weighted tardiness scheduling with sequence-dependent setups: a benchmark library. Technical Report. Intelligent Coordination and Logistics Laboratory. Robotics Institute. Carnegie Mellon University, USA (2003)
8. Lawler, E.L.: A 'pseudopolynomial algorithm for sequencing jobs to minimize total tardiness. Annals of Discrete Mathematics 1, 331-342 (1997)
9. Lee, Y.H., Bhaskaran, K., Pinedo, M.: A heuristic to minimize the total weighted tardiness with sequence-dependent setups. HE Transaction 29, 45-52 (1997)
10. Cicirello, V.A., Smith, S.F.: Enhancing stochastic search performance by value-based randomization of heuristics. Journal of Heuristics 11, 5-34 (2005)
11. Cicirello, V.A.: Non-Wrapping Order Crossover: An Order Preserving Crossover Operator that Respects Absolute Position. In: Proceedings of GECCO 2006 Conference, Seattle, WA, USA, pp. 1125-1131 (2006)
12. Lin, S.-W., Ying, K.-C.: Solving single-machine total weighted tardiness problems with sequence-dependent setup times by meta-heuristies. The International Journal of Advanced Manufacturing Technology (2006)
13. Liao, C.-J., Juan, H.C.: An ant colony optimization for single-machine tardiness scheduling with sequence-dependent setups. Computers & Operations Research 34, 1899-1909 (2007)
14. Dorigo, M., Gambardella, L.M.: Ant colony system: a cooperative learning approach to the traveling salesman problem. IEEE Transactions on Evolutionary Computation 1, 53-66 (1997)
15. Tasgetiren, M.F., Sevkli, M., Liang, Y.-C., Gencyilmaz, G.: Particle swarm optimization algorithm for single machine total weighted tardiness problem. In: Proceedings of the 2004 Congress on Evolutionary Computation (CEC 2004), Portland, Oregon, pp. 1412-1419 (2004)
16. Pinedo, M.: Scheduling: Theory, Algorithms, and Systems. Prentice-Hall, Englewood Cliffs (1995)
17. Anghinolfi, D., Paolucci, M.: A new discrete particle swarm optimization approach for the total tardiness scheduling problem. European Journal of Operational Research (2007)