The capacitated vehicle routing problem with evidential demands
Tài liệu tham khảo
Ben Abdallah, 2014, Combining statistical and expert evidence using belief functions: application to centennial sea level estimation taking into account climate change, Int. J. Approx. Reason., 55, 341, 10.1016/j.ijar.2013.03.008
Agarwal, 2004
Augerat, 1995
Baudrit, 2007, Joint propagation of probability and possibility in risk analysis: towards a formal framework, Int. J. Approx. Reason., 45, 82, 10.1016/j.ijar.2006.07.001
Baudrit, 2006, Joint propagation and exploitation of probabilistic and possibilistic information in risk assessment, IEEE Trans. Fuzzy Syst., 14, 593, 10.1109/TFUZZ.2006.876720
Bertsimas, 2011, Theory and applications of robust optimization, SIAM Rev., 53, 464, 10.1137/080734510
Birge, 1997
Bodin, 1983, Routing and scheduling of vehicles and crews: the state of the art, Comput. Oper. Res., 10, 63, 10.1016/0305-0548(83)90030-8
Brito, 2009, Fuzzy optimization in vehicle routing problems
Charnes, 1958, Cost horizons and certainty equivalents: an approach to stochastic programming of heating oil, Manag. Sci., 4, 235, 10.1287/mnsc.4.3.235
Chen, 2013, Particle swarm optimization for vehicle routing problem with uncertain demand
Christiansen, 2007, A branch-and-price algorithm for the capacitated vehicle routing problem with stochastic demands, Oper. Res. Lett., 35, 773, 10.1016/j.orl.2006.12.009
Couso, 2010, Independence concepts in evidence theory, Int. J. Approx. Reason., 51, 748, 10.1016/j.ijar.2010.02.004
Couso, 2000, A survey of concepts of independence for imprecise probabilities, Risk Decis. Policy, 5, 165, 10.1017/S1357530900000156
Dempster, 1967, Upper and lower probabilities induced by a multivalued mapping, Ann. Math. Stat., 38, 325, 10.1214/aoms/1177698950
Denoeux, 1997, Analysis of evidence-theoretic decision rules for pattern classification, Pattern Recognit., 30, 1095, 10.1016/S0031-3203(96)00137-9
Denoeux, 2009, Extending stochastic ordering to belief functions on the real line, Inf. Sci., 179, 1362, 10.1016/j.ins.2009.01.009
Denoeux, 2016, 40 years of Dempster–Shafer theory, Int. J. Approx. Reason., 79, 1, 10.1016/j.ijar.2016.07.010
Destercke, 2013, Independence and 2-monotonicity: nice to have, hard to keep, Int. J. Approx. Reason., 54, 478, 10.1016/j.ijar.2012.11.002
Destercke, 2015, Ranking of fuzzy intervals seen through the imprecise probabilistic lens, Fuzzy Sets Syst., 278, 20, 10.1016/j.fss.2014.12.009
Destercke, 2011, Idempotent conjunctive combination of belief functions: extending the minimum rule of possibility theory, Inf. Sci., 181, 3925, 10.1016/j.ins.2011.05.007
Destercke, 2015, Cautious label ranking with label-wise decomposition, Eur. J. Oper. Res., 246, 927, 10.1016/j.ejor.2015.05.005
Dror, 1989, Vehicle routing with stochastic demands: properties and solution frameworks, Transp. Sci., 23, 166, 10.1287/trsc.23.3.166
Dubois, 1986, A set-theoretic view of belief functions: logical operations and approximations by fuzzy sets, Int. J. Gen. Syst., 12, 193, 10.1080/03081078608934937
Dubois, 1991, Random sets and fuzzy interval analysis, Fuzzy Sets Syst., 42, 87, 10.1016/0165-0114(91)90091-4
Dubois, 2009, Formal representations of uncertainty, 85
Gauvin, 2014, A branch-cut-and-price algorithm for the vehicle routing problem with stochastic demands, Comput. Oper. Res., 50, 141, 10.1016/j.cor.2014.03.028
Gendreau, 1996, Stochastic vehicle routing, Eur. J. Oper. Res., 88, 3, 10.1016/0377-2217(95)00050-X
Gendreau, 1996, A tabu search heuristic for the vehicle routing problem with stochastic demands and customers, Oper. Res., 44, 469, 10.1287/opre.44.3.469
Glover, 1989, Tabu search-part 1, ORSA J. Comput., 1, 190, 10.1287/ijoc.1.3.190
Glover, 1990, Tabu search-part 2, ORSA J. Comput., 2, 4, 10.1287/ijoc.2.1.4
Harmanani, 2011, A simulated annealing algorithm for the capacitated vehicle routing problem
Helal, 2016, The capacitated vehicle routing problem with evidential demands: a belief-constrained programming approach, vol. 9861, 212
Helal
Helal, 2017, A recourse approach for the capacitated vehicle routing problem with evidential demands, vol. 10369, 190
Holland, 1975
Kirkpatrick, 1983, Optimization by simulated annealing, Science, 220, 671, 10.1126/science.220.4598.671
Laporte, 1992, The vehicle routing problem: an overview of exact and approximate algorithms, Eur. J. Oper. Res., 59, 345, 10.1016/0377-2217(92)90192-C
Laporte, 2002, An integer l-shaped algorithm for the capacitated vehicle routing problem with stochastic demands, Oper. Res., 50, 415, 10.1287/opre.50.3.415.7751
Masri, 2010, Belief linear programming, Int. J. Approx. Reason., 51, 973, 10.1016/j.ijar.2010.07.003
Mourelatos, 2006, A design optimization method using evidence theory, J. Mech. Des., 128, 901, 10.1115/1.2204970
Peng, 2010, Vehicle routing problem with fuzzy demands and the particle swarm optimization solution
Pichon, 2012, Relevance and truthfulness in information correction and fusion, Int. J. Approx. Reason., 53, 159, 10.1016/j.ijar.2011.02.006
Quaeghebeur, 2012, Constrained optimization problems under uncertainty with coherent lower previsions, Fuzzy Sets Syst., 206, 74, 10.1016/j.fss.2012.02.004
Sengupta, 1970, A generalization of some distribution aspects of chance-constrained linear programming, Int. Econ. Rev., 11, 287, 10.2307/2525670
Shafer, 1976
Srivastava, 2013, An evolutionary algorithm based approach to design optimization using evidence theory, J. Mech. Des., 135, 10.1115/1.4024223
Sungur, 2008, A robust optimization approach for the capacitated vehicle routing problem with demand uncertainty, IIE Trans., 40, 509, 10.1080/07408170701745378
Teodorovic, 1996, The fuzzy set theory approach to the vehicle routing problem when demand at nodes is uncertain, Fuzzy Sets Syst., 82, 307, 10.1016/0165-0114(95)00276-6
Toth, 2002, An overview of vehicle routing problems, 1
Troffaes, 2007, Decision making under uncertainty using imprecise probabilities, Int. J. Approx. Reason., 45, 17, 10.1016/j.ijar.2006.06.001
Walley, 1991, Statistical Reasoning with Imprecise Probabilities, 10.1007/978-1-4899-3472-7
Zadeh, 1999, Fuzzy sets as a basis for a theory of possibility, Fuzzy Sets Syst., 100, 9, 10.1016/S0165-0114(99)80004-9