[1]
Abd Aziz Z & Kendall G. An Investigation of an Ant-based Hyper-heuristic for the Capacitated Vehicle Routing Problem. In Proceedings of Multidiciplinary International Conference on Scheduling: Theory and Applications (MISTA), (2009).
Google Scholar
[2]
Bullnheimer B., Hartl R.F. & Strauss C. Applying the Ant System to the Vehicle Routing Problem, In MetaHeuristics: Advances and Trends in Local Search Paradigms for Optimization, Kluwer Academic, 1999a.
DOI: 10.1007/978-1-4615-5775-3_20
Google Scholar
[3]
Bullnheimer B., Hartl R. F. & Strauss C. A New Rank Based Version of the Ant System - A Computational Study. In Central European Journal of Operations Research, (volume 7, pp.25-38), 1999b.
Google Scholar
[4]
Burke E. K., Kendall G., Landa-Silva J. D., O'Brien R. & Soubeiga E. An Ant Algorithm Hyperheuristic for the Project Presentation Scheduling Problem. In Proceedings of the 2005 IEEE Congress on Evolutionary Computation, (volume 3, pp.2263-2270.
DOI: 10.1109/cec.2005.1554976
Google Scholar
[5]
Burke E.K., Kendall G., Newall J., Hart E. & Ross P. Hyper-heuristics: An Emerging Direction in Modern Search Technology. In Glover F. & Kochenberger G.A. (eds), Handbook of Metaheuristics (pp.457-474). Kluwer Academic Publishers, 2003b.
DOI: 10.1007/0-306-48056-5_16
Google Scholar
[6]
Burke E.K., Kendall G., O'Brien R.F.J., Redrup D. & Soubeiga E. An Ant Algorithm Hyper-heuristic. In Proceedings of the Fifth Meta-heuristics International Conference (MIC2003), 2003c.
Google Scholar
[7]
Braysy O. & Gendreau M. Vehicle Routing Problem with Time Windows, Part I: Route Construction and Local Search Algorithms. In Transportation Science, (volume 39, pp.104-118), 2005a.
DOI: 10.1287/trsc.1030.0056
Google Scholar
[8]
Chen P. Hyper-heuristic Ant Algorithm for the Traveling Tournament Problem. PhD Thesis. University of Nottingham, UK., (2006).
Google Scholar
[9]
Chen P., Kendall G. & Berghe G.V. An Ant Based Hyper-heuristic for the Travelling Tournament Problem. In Proceedings of IEEE Symposium of Computational Intelligence in Scheduling (CISched 2007), (pp.19-26), (2007).
DOI: 10.1109/scis.2007.367665
Google Scholar
[10]
Cordeau J-F. & Laporte G. Tabu Search Heuristics for Vehicle Routing Problem. In Metaheuristic Optimization via Memory and Evolution, (volume 30, pp.145-163), (2005).
DOI: 10.1007/0-387-23667-8_6
Google Scholar
[11]
Cowling P., Kendall G. & Soubeiga E. Hyperheuristics: A Robust Optimisation Method Applied to Nurse Scheduling. In Seventh International Conference on Parallel Problem Solving from Nature, PPSN, (pp.851-860). LCNS Springer, 2002a.
DOI: 10.1007/3-540-45712-7_82
Google Scholar
[12]
Crowston W.B., Glover F., Thompson G.L. & Trawick J.D. Probabilistic and Parametric Learning Combinations of Local Job Shop Scheduling Rules. In ONR research memorandum. Cernegie-Mellon University Pittsburgh, (1963).
DOI: 10.21236/ad0600965
Google Scholar
[13]
Dantzig G.B. & Ramser J.H. The Truck Dispatching Problem. In Management Science, (volume 6(1), pp.80-91), (1959).
DOI: 10.1287/mnsc.6.1.80
Google Scholar
[14]
Dorigo M. & Stutzle T. Handbook of Metaheuristics, Glover F. & Kochenberger G.A. (eds) (pp.251-285). Kluwer Academic Publishers, 2003a.
Google Scholar
[15]
Dorigo M. & Di Caro G. Ant Algorithms for Discrete Optimization. Artificial Life, (volume 5, pp.137-172), 1999a.
Google Scholar
[16]
Dorigo M. & Di Caro G. The Ant Colony Optimization Meta-heuristic. New Ideas in Optimization (pp.11-32). Mc Graw Hill, 1999b.
Google Scholar
[17]
Dorigo M. & Di Caro G. Ant Colony Optimization: A New Meta-heuristic. In Proceedings of the Congress on Evolutionary Computation, (pp.1470-1477). IEEE Press, 1999c.
DOI: 10.1109/cec.1999.782657
Google Scholar
[18]
Dorigo M. & Gambardella L. M. Ant Colony System: A Cooperative Learning Approach to the Travelling Salesman Problem. In IEEE Transaction on Evolutionary Computation, (volume 1, pp.53-66), (1997).
DOI: 10.1109/4235.585892
Google Scholar
[19]
Dorigo M., Maniezzo V. & Colorni A. Positive feedback as a Search Strategy. In Technical Report No 91-016. Dipartimento di Eletronica, Politecnico di Milano, Italy, (1991).
Google Scholar
[20]
Dorigo M., Maniezzo V. & Colorni A. Ant system: Optimisation by a Colony of Cooperating Agents. In IEEE Transactions on Systems, Man and Cybernetics, (p.26, 29-41), (1996).
DOI: 10.1109/3477.484436
Google Scholar
[21]
Dorigo M., Maniezzo V. & Colorni A. Positive feedback as a Search Strategy. In Technical Report No 91-016. Dipartimento di Eletronica, Politecnico di Milano, Italy, (1991).
Google Scholar
[22]
Fisher H & Thompson G.L. Probabilistic Learning Combinations of Local Job-shop Scheduling Rules. In Factory Scheduling Conference. Carnegie Institute of Technology, (1961).
Google Scholar
[23]
Fisher H & Thompson G.L. Probabilistic Learning Combinations of Local Job-shop Scheduling Rules. In J.F. Muth & G.L. Thompson (eds), Industrial Scheduling, (pp.225-251). Prentice-Hall, Inc, New Jersey, (1963).
DOI: 10.21236/ad0600965
Google Scholar
[24]
O'Brien R.F.J. Ant Algorithm Hyperheuristic Approaches for Scheduling Problems. PhD Thesis, University of Nottingham. UK, (2007).
Google Scholar
[25]
Soubeiga E. Development and Application of Hyperheuristics to Personnel Scheduling. PhD thesis. School of Computer Science and Information Technology, University of Nottingham, (2003).
Google Scholar
[26]
Stutzle T. & Dorigo M. ACO Algorithms for the Quadratic Assignment Problem. New Ideas in Optimization (pp.33-50), McGraw Hill, (1999).
Google Scholar
[27]
Vehicle Routing Datasets. Website: http: /www. coin-r. org/SYMPHONY/branchandcut/ VRP/data, (2003).
Google Scholar