A hybrid differential evolution algorithm to vehicle routing problem with fuzzy demands

Journal of Computational and Applied Mathematics

Volumn 231, Issue 1, 2009, Pages 302-310

  Erbao, Cao ^a,b   Mingyong, Lai ^a,b  

^a HUNAN UNIVERSITY   (China)

^b Hunan Province Laboratory of Logistics Information and Simulation Technology   (China)

Author keywords

Differential evolution; Fuzzy sets; Optimization; Stochastic simulation; Uncertainty; Vehicle routing problem

Indexed keywords

BEST VALUE; CHANCE-CONSTRAINED; CREDIBILITY THEORY; DIFFERENTIAL EVOLUTION; DIFFERENTIAL EVOLUTION ALGORITHMS; FINAL OBJECTIVE; FUZZY DEMAND; HYBRID DIFFERENTIAL EVOLUTION ALGORITHM; HYBRID INTELLIGENT ALGORITHMS; PROGRAM MODELS; STOCHASTIC SIMULATION; STOCHASTIC SIMULATIONS; UNCERTAINTY; VEHICLE ROUTING PROBLEM; VEHICLE ROUTING PROBLEMS;

DAMPING; FUZZY SETS; RANDOM PROCESSES; ROUTING ALGORITHMS; SIMULATORS; STOCHASTIC CONTROL SYSTEMS; STOCHASTIC MODELS; VEHICLE ROUTING; VEHICLES;

EVOLUTIONARY ALGORITHMS;

EID: 67349132233     PISSN: 03770427     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cam.2009.02.015     Document Type: Article

References (21)

1. Dantzing G., and Ramser J. The truck dispatching problem. Management Science 10 6 (1959) 80-91
2. Bertsimas D.J. A vehicle routing problem with stochastic demand. Operational Research 40 (1992) 574-585
3. Dror M., Laporte G., and Trudeau P. Vehicle routing with stochastic demands: Properties and solution frameworks. Transportation Science 23 (1989) 166-176
4. Gendreau M., Laporate G., and Seguin R. Stochastic vehicle routing. European Journal of Operational Research 88 (1996) 3-12
5. Liu B., and Lai K.K. Stochastic programming models for vehicle routing problems. Asian Information Science Life 1 1 (2002) 13-28
6. Teodorovic D., and Pavkovic G. The fuzzy set theory approach to the vehicle routing problem when demand at nodes is uncertain. Fuzzy Sets and Systems 82 (1996) 307-317
7. Cheng R., and Gen M. Vehicle routing problem with fuzzy due-time using genetic algorithm. Japanese Journal of Fuzzy Theory and Systems 7 5 (1995) 1050-1061
8. K.K. Lai, B. Liu, J. Peng, Vehicle routing problem with fuzzy travel times and its genetic algorithm, Technical Report, 2003
9. Zheng Y., and Liu B. Fuzzy vehicle routing model with credibility measure and its hybrid intelligent algorithm. Applied Mathematics and Computation 176 (2006) 673-683
10. R. Storn, K. Price, Differential evolution - a simple and efficient adaptive scheme for global optimization over continuous spaces, Technical Report TR-95-012, ICSI, March 1995. ftp.icsi.berkeley.edu
11. Storn R. Differential evolution design of an IIR-filter. Proceedings IEEE Conference Evolutionary Computation (1996), IEEE, Nagoya, Japan 268-273
12. Nearchou A.C. Meta-heuristics from nature for the loop layout design problem. International Journal of Production Economics 101 2 (2006) 312-328
13. Lampinen J., and Zelinka I. Mechanical engineering design optimization by differential evolution. In: Corne D., Dorigo M., and Glover F. (Eds). New Ideas in Optimization (1999), McGraw-Hill, London, UK 127-146
14. Zadeh L.A. Fuzzy Sets, Information and Control 8 (1965) 338-353
15. Kaufman A. Introduction to the Theory of Fuzzy Subsets (1975), Academic Press, New York
16. Zadeh L.A. Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems 1 (1978) 3-28
17. Liu B. Uncertain Theory: An Introduce to its Axiomatic Foundations (2004), Springer, Berlin
18. Gen M., and Cheng R. Genetic Algorithm and Engineering Design (1997), John Wiley and Sons, Inc., New York
19. Qian B., et al. An effective hybrid DE-based algorithm for multi-objective flow shop scheduling with limited buffers. Computers and Operations Research (2007) 10.1016/j.cor.2007.08.007
20. Onwubolu G., and Davendra D. Scheduling flow shops using differential evolution algorithm. European Journal of Operational Research 171 (2006) 674-692
21. DE Home page. http://www.icsi.berkeley.edu/~storn/code.html