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A mixed integer programming model for solving real-time truck-to-door assignment and scheduling problem at cross docking warehouse
Location and capacity design of congested intermediate facilities in networks
1. | School of Management, South-Central University for Nationalities, Wuhan, 430074, China |
2. | Department of Automation, School of Power and Mechanical Engineering, Wuhan University, Wuhan, 430072, China |
References:
[1] |
R. Aboolian, O. Berman and D. Krass, Profit maximizing distributed service system design with congestion and elastic demand,, Transportation Science, 46 (2012), 247.
doi: 10.1287/trsc.1110.0392. |
[2] |
S.R. Agnihothri, S. Narasimhan and H. Pirkul, An assignment problem with queueing time cost,, Naval Research Logistics, 37 (1990), 231.
doi: 10.1002/1520-6750(199004)37:2<231::AID-NAV3220370204>3.0.CO;2-N. |
[3] |
M. Armony, E. Plambeck and S. Seshadri, Sensitivity of optimal capacity to customer impatience in an unobservable m/m/s queue (why you shouldn't shout at the dmv),, Manufacturing & Service Operations Management, 11 (2009), 19.
doi: 10.1287/msom.1070.0194. |
[4] |
O. Berman and Z. Drezner, Location of congested capacitated facilities with distance-sensitive demand,, IIE Transactions, 38 (2006), 213.
doi: 10.1080/07408170500288190. |
[5] |
O. Berman and Z. Drezner, The multiple server location problem,, Journal of the Operational Research Society, 58 (2006), 91.
doi: 10.1057/palgrave.jors.2602126. |
[6] |
M. L. Brandeau and S. S. Chiu, A center location problem with congestion,, Annals of operations research, 40 (1992), 17.
doi: 10.1007/BF02060468. |
[7] |
M. L. F. Cheong, R. Bhatnagar and S. C. Graves, Logistics network design with supplier consolidation hubs and multiple shipment options,, Journal of Industrial and Management Optimization, 3 (2007), 51.
doi: 10.3934/jimo.2007.3.51. |
[8] |
S. M. Choi, X. Huang and W. K. Ching, Minimizing equilibrium expected sojourn time via performance-based mixed threshold demand allocation in a multiple-server queueing environment,, Journal of Industrial and Management Optimization, 8 (2012), 299.
doi: 10.3934/jimo.2012.8.299. |
[9] |
M. S. Daskin, C. R. Coullard and Z.-J. M. Shen, A maximum expected covering location model: formulation, properties and heuristic solution,, Transportation Science, 17 (1983), 48.
doi: 10.1287/trsc.17.1.48. |
[10] |
M. S. Daskin, C. R. Coullard and Z.-J. M. Shen, An inventory-location model: Formulation, solution algorithm and computational results,, Annals of Operations Research, 110 (2002), 83.
doi: 10.1023/A:1020763400324. |
[11] |
M. S. Daskin, Network and Discrete Location: Models, Algorithms, and Applications,, John Wiley & Sons, (2011).
doi: 10.1002/9781118032343. |
[12] |
S. Elhedhli and H. Wu, A lagrangean heuristic for hub-and-spoke system design with capacity selection and congestion,, INFORMS Journal on Computing, 22 (2010), 282.
doi: 10.1287/ijoc.1090.0335. |
[13] |
A. F. Gabor and J. Van Ommeren, An approximation algorithm for a facility location problem with stochastic demands and inventories,, Operations research letters, 34 (2006), 257.
doi: 10.1016/j.orl.2005.04.009. |
[14] |
R. Hassin and M. Haviv, To Queue or not to Queue: Equilibrium Behavior in Queueing Systems,, Kluwer Academic Publishers, (2002).
doi: 10.1007/978-1-4615-0359-0. |
[15] |
D. Hu, C. Yang and J. Yang, Budget constrained flow interception location model for congested systems,, Journal of Systems Engineering and Electronics, 20 (2009), 1255. Google Scholar |
[16] |
S. Huang, R. Batta and R. Nagi, Distribution network design: Selection and sizing of congested connections,, Naval Research Logistics, 52 (2005), 701.
doi: 10.1002/nav.20106. |
[17] |
V. Marianov and D. Serra, Probabilistic, maximal covering location-allocation models for congested systems,, Journal of Regional Science, 38 (1998), 401. Google Scholar |
[18] |
S. H. R. Pasandideh, S. T. A. Niaki and V. Hajipour, A multi-objective facility location model with batch arrivals: two parameter-tuned meta-heuristic algorithms,, Journal of Intelligent Manufacturing, 24 (2013), 331. Google Scholar |
[19] |
S. H. A. Rahmati, A. Ahmadi, M. Sharifi and A. Chambari, A multi-objective model for Facility Location-allocation Problem with immobile servers within queuing framework,, Computers and Industrial Engineering, 74 (2014), 1.
doi: 10.1016/j.cie.2014.04.018. |
[20] |
H. Shavandi and H. Mahlooji, A fuzzy queuing location model with a genetic algorithm for congested systems,, Applied mathematics and computation, 181 (2006), 440.
doi: 10.1016/j.amc.2005.12.058. |
[21] |
Q. Wang, R. Batta and C. M. Rump, Algorithms for a facility location problem with stochastic customer demand and immobile servers,, Annals of Operations Research, 111 (2002), 17.
doi: 10.1023/A:1020961732667. |
[22] |
Q. Wang, R. Batta and C. M. Rump, Facility location models for immobile servers with stochastic demand,, Naval Research Logistics, 51 (2004), 137.
doi: 10.1002/nav.10110. |
[23] |
L. Zhang and G. Rushton, Optimizing the size and locations of facilities in competitive multi-site service systems,, Computers & Operations Research, 35 (2008), 327.
doi: 10.1016/j.cor.2006.03.002. |
show all references
References:
[1] |
R. Aboolian, O. Berman and D. Krass, Profit maximizing distributed service system design with congestion and elastic demand,, Transportation Science, 46 (2012), 247.
doi: 10.1287/trsc.1110.0392. |
[2] |
S.R. Agnihothri, S. Narasimhan and H. Pirkul, An assignment problem with queueing time cost,, Naval Research Logistics, 37 (1990), 231.
doi: 10.1002/1520-6750(199004)37:2<231::AID-NAV3220370204>3.0.CO;2-N. |
[3] |
M. Armony, E. Plambeck and S. Seshadri, Sensitivity of optimal capacity to customer impatience in an unobservable m/m/s queue (why you shouldn't shout at the dmv),, Manufacturing & Service Operations Management, 11 (2009), 19.
doi: 10.1287/msom.1070.0194. |
[4] |
O. Berman and Z. Drezner, Location of congested capacitated facilities with distance-sensitive demand,, IIE Transactions, 38 (2006), 213.
doi: 10.1080/07408170500288190. |
[5] |
O. Berman and Z. Drezner, The multiple server location problem,, Journal of the Operational Research Society, 58 (2006), 91.
doi: 10.1057/palgrave.jors.2602126. |
[6] |
M. L. Brandeau and S. S. Chiu, A center location problem with congestion,, Annals of operations research, 40 (1992), 17.
doi: 10.1007/BF02060468. |
[7] |
M. L. F. Cheong, R. Bhatnagar and S. C. Graves, Logistics network design with supplier consolidation hubs and multiple shipment options,, Journal of Industrial and Management Optimization, 3 (2007), 51.
doi: 10.3934/jimo.2007.3.51. |
[8] |
S. M. Choi, X. Huang and W. K. Ching, Minimizing equilibrium expected sojourn time via performance-based mixed threshold demand allocation in a multiple-server queueing environment,, Journal of Industrial and Management Optimization, 8 (2012), 299.
doi: 10.3934/jimo.2012.8.299. |
[9] |
M. S. Daskin, C. R. Coullard and Z.-J. M. Shen, A maximum expected covering location model: formulation, properties and heuristic solution,, Transportation Science, 17 (1983), 48.
doi: 10.1287/trsc.17.1.48. |
[10] |
M. S. Daskin, C. R. Coullard and Z.-J. M. Shen, An inventory-location model: Formulation, solution algorithm and computational results,, Annals of Operations Research, 110 (2002), 83.
doi: 10.1023/A:1020763400324. |
[11] |
M. S. Daskin, Network and Discrete Location: Models, Algorithms, and Applications,, John Wiley & Sons, (2011).
doi: 10.1002/9781118032343. |
[12] |
S. Elhedhli and H. Wu, A lagrangean heuristic for hub-and-spoke system design with capacity selection and congestion,, INFORMS Journal on Computing, 22 (2010), 282.
doi: 10.1287/ijoc.1090.0335. |
[13] |
A. F. Gabor and J. Van Ommeren, An approximation algorithm for a facility location problem with stochastic demands and inventories,, Operations research letters, 34 (2006), 257.
doi: 10.1016/j.orl.2005.04.009. |
[14] |
R. Hassin and M. Haviv, To Queue or not to Queue: Equilibrium Behavior in Queueing Systems,, Kluwer Academic Publishers, (2002).
doi: 10.1007/978-1-4615-0359-0. |
[15] |
D. Hu, C. Yang and J. Yang, Budget constrained flow interception location model for congested systems,, Journal of Systems Engineering and Electronics, 20 (2009), 1255. Google Scholar |
[16] |
S. Huang, R. Batta and R. Nagi, Distribution network design: Selection and sizing of congested connections,, Naval Research Logistics, 52 (2005), 701.
doi: 10.1002/nav.20106. |
[17] |
V. Marianov and D. Serra, Probabilistic, maximal covering location-allocation models for congested systems,, Journal of Regional Science, 38 (1998), 401. Google Scholar |
[18] |
S. H. R. Pasandideh, S. T. A. Niaki and V. Hajipour, A multi-objective facility location model with batch arrivals: two parameter-tuned meta-heuristic algorithms,, Journal of Intelligent Manufacturing, 24 (2013), 331. Google Scholar |
[19] |
S. H. A. Rahmati, A. Ahmadi, M. Sharifi and A. Chambari, A multi-objective model for Facility Location-allocation Problem with immobile servers within queuing framework,, Computers and Industrial Engineering, 74 (2014), 1.
doi: 10.1016/j.cie.2014.04.018. |
[20] |
H. Shavandi and H. Mahlooji, A fuzzy queuing location model with a genetic algorithm for congested systems,, Applied mathematics and computation, 181 (2006), 440.
doi: 10.1016/j.amc.2005.12.058. |
[21] |
Q. Wang, R. Batta and C. M. Rump, Algorithms for a facility location problem with stochastic customer demand and immobile servers,, Annals of Operations Research, 111 (2002), 17.
doi: 10.1023/A:1020961732667. |
[22] |
Q. Wang, R. Batta and C. M. Rump, Facility location models for immobile servers with stochastic demand,, Naval Research Logistics, 51 (2004), 137.
doi: 10.1002/nav.10110. |
[23] |
L. Zhang and G. Rushton, Optimizing the size and locations of facilities in competitive multi-site service systems,, Computers & Operations Research, 35 (2008), 327.
doi: 10.1016/j.cor.2006.03.002. |
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