A modified artificial bee colony algorithm for vehicle routing problems with time windows

Information Technology Journal

Volumn 11, Issue 10, 2012, Pages 1490-1495

  Shi, Yan Jun ^a   Meng, Fan Wei ^a   Shen, Guo Jiang ^a  

^a DALIAN UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

Artificial bee colony algorithm; Time windows; Tournament selection; Vehicle routing

Indexed keywords

ARTIFICIAL BEE COLONY ALGORITHMS; FOOD SOURCES; GLOBAL SEARCH; NEIGHBORHOOD SEARCH; NEW SOLUTIONS; STATE-OF-THE-ART ALGORITHMS; TIME WINDOWS; TOURNAMENT SELECTION; VEHICLE ROUTING PROBLEMS;

COMPUTATIONAL COMPLEXITY; HEURISTIC ALGORITHMS; NETWORK ROUTING; ROUTING ALGORITHMS;

VEHICLE ROUTING;

EID: 84863441094     PISSN: 18125638     EISSN: 18125646     Source Type: Journal    
DOI: 10.3923/itj.2012.1490.1495     Document Type: Article

References (34)

1. Abu-Mouti, F.S. and M.E. El-Hawary, 2011. Optimal distributed generation allocation and sizing in distribution systems via artificial bee colony algorithm. IEEE Transac. Power Delivery, 26: 2090-2101.
2. Baldacci, R., E. Bartolini and A. Mingozzi, 2011. An exact algorithm for the pickup and delivery problem with time windows. Oper. Res., 59: 414-426.
3. Balseiro, S.R., I. Loiseau and J. Ramonet, 2011. An ant colony algorithm hybridized with insertion heuristics for the time dependent vehicle routing problem with time windows. Comput. Oper. Res., 38: 954-966.
4. Bettmelh, A., A. Ceselh and G. Righini, 2011. A branch-and-cut-and-price algorithm for the multi-depot heterogeneous vehicle routing problem with time windows. Transp. Res. Part C Emerg. Technol., 19: 723-740.
5. Bramel, J. andD. Simchi-Levi, 1996. Probabilistic analyses and practical algorithms for the vehicle routing problem with time windows. Oper. Res., 44: 501-509. (Pubitemid 126669515)
6. Chang, Y.C. and W.T. Huang, 2011. A modification of simplified drum-buffer-rope for re-entrant flow shop scheduling. Inform. Technol. J., 10: 40-50.
7. Chen, J.S., 2010. Integration of job scheduling with delivery vehicles routing. Inform. Technol. J., 9: 1202-1206.
8. Chiu, M.C., 2010. Numerical assessment of path planning for an autonomous robot passing through multi-layer barrier systems using a genetic algorithm. Inform. Technol. J., 9: 1483-1489.
9. Cordeau, J.F. and M. Maischberger, 2011. A parallel iterated tabu search heuristic for vehicle routing problems. Comput. Oper. Res., 39: 2033-2050.
10. Cormen, T.H., C.E. Leiserson and R.L. Rivest, 1990. Introduction to Algorithms. MIT Press, Cambridge, MA.
11. Dantzig, G.B. and J.H. Ramser, 1959. The truck dispatching problem. Manage. Sci., 6: 80-91.
12. Dong-Feng, W. and X. Feng, 2010. Multi-objective optimization problems with arena principle and NSGA-II. Inform. Technol. J., 9: 381-385.
13. Figliozzi, M.A., 2010. An iterative route construction and improvement algorithm for the vehicle routing problem with soft time windows. Trans. Res. Part C: Emerging Technol, 18: 668-679.
14. Ghoseiri, K. and S.F. Ghannadpour, 2009. Hybrid genetic algorithm for vehicle routing and scheduling problem. J. Applied Sci., 9: 79-87.
15. Hashimoto, H., M. Yagiura and T. Ibaraki, 2008. An iterated local search algorithm for the time-dependent vehicle routing problem with time windows. Discrete Optim., 5: 434-456. (Pubitemid 351443152)
16. Ibrahim, A.A., 2007. Graph algorithms and shortest path problems: A case of Djikstra1 s algorithm and the dual carriage ways in Sokoto metropolis. Trends Applied Sci. Res., 2: 348-353.
17. Karaboga, D. and C. Ozturk, 2009. Neural networks training by artificial bee colony algorithm on pattern classification. Neural Network World, 19: 279-292.
18. Karaboga, D., 2005. An idea based on honey bee swarm for numerical optimization. Technical Report-TR06, Erciyes University, Engineering Faculty, Computer Engineering Department, Kayseri/Turkiye. http://inf.erciyes.edu.tr/abc/ pub/tr06-2005.pdf
19. Liu, C.S. and F.H. Huang, 2010. An effective genetic algorithm for the vehicle routing problem with time windows. Key Eng. Mat., 439: 247-250.
20. Luo, H., Y. Lv, X. Deng and H. Zhang, 2009. Optimization of adaptation gains of full-order flux observer in sensorless induction motor drives using genetic algorithm. Inform. Technol. J., 8: 577-582.
21. Miller, B.L. and D.E. Goldberg, 1996. Genetic algorithms, selection schemes and the varying effects of noise. Evolut. Comput, 4: 113-131. (Pubitemid 126706153)
22. Moccia, L., J.F. Cordeau and G. Laporte, 2011. An incremental tabu search heuristic for the generalized vehicle routing problem with time windows. J. Operat. Res. Soc, 63: 232-244.
23. Pavone, M., N. Bisnik, E. Frazzoh and V. Isler, 2009. A stochastic and dynamic vehicle routing problem with time windows and customer impatience. Mobile Networks Applicat, 14: 350-364.
24. Pureza, V. and R. Morabito, 2011. Vehicle routing with multiple deliverymen: Modeling and heuristic approaches for the VRPTW. Europ. J. Operat. Res., 211: 35-46.
25. Russell, R.A. and W.C. Chiang, 2006. Scatter search for the vehicle routing problem with time windows. Europ. J. Operat. Res., 169: 606-622. (Pubitemid 41375710)
26. Sadouni, K., 2006. Heterogeneous fleet vehicle routing problem with time windows and nonlinearly penalized delays. J. Applied Sci., 6: 1969-1973. (Pubitemid 44540598)
27. Sharma, S., R.C. Jain and S.S. Bhadauria, 2006. Simulation study of congestion adaptive routing algorithm for mobile Ad hoc network. Trends Applied Sci. Res., 1: 368-378.
28. Shi, Y., B. Li andZ. Zihui, 2011. Layout design of satellite module using a modified artificial bee colony Algorithm. Adv. Sci. Lett, 8: 3178-3181.
29. Solomon, M.M., 1987. Algorithms for the vehicle routing and scheduling problems with time window constraints. Operat. Res., 35: 254-265.
30. Tan, K.C., L.H. Lee, K.Q. Zhu and K. Qu, 2001. Heuristic methods for vehicle routing problem with time windows. Artificial Intell. Eng., 15: 281-295. (Pubitemid 33039202)
31. Wasan, S.A., 2008. Finding linear equivalence of keystream generators using genetic simulated annealing. Inform. Technol. J., 7: 541-544.
32. Wu, X., S. Ma and Y. Shi, 2011. Fuel consumption optimization for vehicle routing problem with time windows. J. Convergence Inform. Technol., 6: 332-338.
33. Zhen, T., Q. Zhang, W. Zhang and Z. Ma, 2008. Hybrid ant colony Algorithm for the vehicle routing with time windows. ISECS Int. Colloquium Comput. Commnn. Control Manage., 1: 8-12.
34. Zielonka, A., E. Hetmaniok and D. Slota, 2011. Using the artificial bee colony algorithm for determining the heat transfer coefficient. Man-Machine Interac, 2: 369-376.