Swarm intelligence applied in green logistics: A literature review

Engineering Applications of Artificial Intelligence

Volumn 37, Issue , 2015, Pages 154-169

  Zhang, Shuzhu ^a   Lee, C K M ^a   Chan, H K ^b   Choy, K L ^a   Wu, Zhang ^c  

^a HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

^b UNIVERSITY OF NOTTINGHAM   (United Kingdom)

^c NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

Closed loop supply chain; Green logistics; Literature review; Optimization; Reverse logistics; Swarm intelligence

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMBINATORIAL OPTIMIZATION; HEURISTIC METHODS; LOGISTICS; OPTIMIZATION; SUPPLY CHAINS;

CLOSED-LOOP SUPPLY CHAIN; GREEN LOGISTICS; LITERATURE REVIEWS; REVERSE LOGISTICS; SWARM INTELLIGENCE;

PROBLEM SOLVING;

EID: 84910607489     PISSN: 09521976     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.engappai.2014.09.007     Document Type: Article

References (194)

1. Abbass, H.A., 2001. MBO: Marriage in honey bees optimization - A haplometrosis polygynous swarming approach. In: Proceedings of the 2001 IEEE Congress on Evolutionary Computation, pp. 207-214.
2. E.B.E.I. Adiba, M. Elhassania, and E.H.A. Ahemd A Hybrid Ant Colony System for Green capacitated vehicle routing problem in sustainbale transport J. Theor. Appl. Inf. Technol. 54 2013 198 208
3. G. Agarwal, S. Barari, and M.K. Tiwari A PSO-based optimum consumer incentive policy for WEEE incorporating reliability of components Int. J. Prod.Res. 50 2012 4372 4380
4. S. Agrawal, and M.K. Tiwari A collaborative ant colony algorithm to stochastic mixed-model U-shaped disassembly line balancing and sequencing problem Int. J. Prod. Res. 46 2007 1405 1429
5. B. Akay, and D. Karaboga Artificial bee colony algorithm for large-scale problems and engineering design optimization J. Intell. Manuf. 23 2012 1001 1014
6. A. Alvarado-Iniesta, J.L. Garcia-Alcaraz, M.I. Rodriguez-Borbon, and A. Maldonado Optimization of the material flow in a manufacturing plant by use of artificial bee colony algorithm Expert Syst. Appl. 40 2013 4785 4790
7. A. Asef-Vaziri, M. Kazemi, K. Eshghi, and M. Lahmar An ant colony system for enhanced loop-based aisle-network design Eur. J. Oper. Res. 207 2010 110 120
8. A. Askarzadeh, and A. Rezazadeh A new heuristic optimization algorithm for modeling of proton exchange membrane fuel cell: bird mating optimizer Int. J. Energy Res. 37 2013 1196 1204
9. S.R. Balseiro, I. Loiseau, and J. Ramonet An ant colony algorithm hybridized with insertion heuristics for the time dependent vehicle routing problem with time windows Comput. Oper. Res. 38 2011 954 966
10. J. Bautista, and J. Pereira Modeling the problem of locating collection areas for urban waste management. An application to the metropolitan area of Barcelona. Omega 34 2006 617 629
11. J.E. Bell, and S.E. Griffis Swarm intelligence: application of the ant colony optimization algorithm to logistics-oriented vehicle routing problems J. Bus. Logist. 31 2010 157 175
12. J.E. Bell, and P.R. McMullen Ant colony optimization techniques for the vehicle routing problem Adv. Eng. Inf. 18 2004 41 48
13. G. Beni, and J. Wang Swarm Intelligence in Cellular Robotic Systems, Robots and Biological Systems: Towards a New Bionics? 1993 Springer Berlin Heidelberg 703 712
14. M. Björklund, U. Martinsen, and M. Abrahamsson Performance measurements in the greening of supply chains Supply Chain Manag. 17 2012 29 39
15. C. Blum, and X. Li Swarm intelligence in optimization C. Blum, D. Merkle, Swarm Intelligence 2008 Springer Berlin Heidelberg 43 85
16. C. Blum, and D. Merkle Swarm intelligence: introduction and applications 2008 Springer Berlin Heidelberg
17. C. Blum, and A. Roli Metaheuristics in combinatorial optimization: Overview and conceptual comparison ACM Comput. Surveys (CSUR) 35 2003 268 308
18. D.D. Bochtis, and C.G. Sørensen The vehicle routing problem in field logistics: Part II Biosyst. Eng. 105 2010 180 188
19. E. Bonabeau, M. Dorigo, and G. Theraulaz Swarm intelligence: from natural to artificial systems 1999 Oxford university press New York
20. J. Branke, and M. Guntsch Solving the probabilistic TSP with ant colony optimization J. Math. Model. Algor. 3 2005 403 425
21. P.M. Brewerton, and L.J. Millward Organizational research methods: A guide for students and researchers 2001 Sage London
22. I. Budinská, T. Kasanický, and J. Zelenka Production planning and scheduling by means of artificial immune systems and particle swarm optimisation algorithms Int. J. Bio-Inspir. Comput. 4 2012 237 248
23. O. Bulut, and M.F. Tasgetiren An artificial bee colony algorithm for the economic lot scheduling problem Int. J. Prod. Res. 52 2013 1150 1170
24. G.G. Cabrera, E. Cabrera, R. Soto, L.J.M. Rubio, B. Crawford, and F. Paredes A hybrid approach using an artificial bee algorithm with mixed integer programming applied to a large-scale capacitated facility location problem Math. Prob. Eng. 2012 2012 14
25. B. Çatay A new saving-based ant algorithm for the vehicle routing problem with simultaneous pickup and delivery Expert Syst. Appl. 37 2010 6809 6817
26. Z.H. Che Using fuzzy analytic hierarchy process and particle swarm optimisation for balanced and defective supply chain problems considering WEEE/RoHS directives Int. J. Prod. Res. 48 2009 3355 3381
27. Z.H. Che, T.A. Chiang, and Y.C. Kuo Multi-echelon reverse supply chain network design with specified returns using particle swarm optimization Int. J. Innov. Comput., Inf. Control 8 2012 6719 6731
28. C.-H. Chen, and C.-J. Ting An improved ant colony system algorithm for the vehicle routing problem J. Chin. Inst. Ind. Eng. 23 2006 115 126
29. C.-H. Chen, and C.-J. Ting Combining Lagrangian heuristic and Ant Colony System to solve the Single Source Capacitated Facility Location Problem Transp. Res. Part E: Logist. Transp. Rev. 44 2008 1099 1122
30. K.-H. Chen, and C.-T. Su Activity assigning of fourth party logistics by particle swarm optimization-based preemptive fuzzy integer goal programming Expert Syst. Appl. 37 2010 3630 3637
31. T.G. Chen, and C.H. Ju A novel artificial bee colony algorithm for solving the supply chain network design under disruption scenarios Int. J. Comput. Appl. Technol. 47 2013 289 296
32. Chen, Y., Liu, D., 2013. An Uncertain Programming Model for Manufacturing/Remanufacturing Hybrid System in Reverse Logistics Environment, Wuhan, pp. 251-255.
33. C.S. Chong, L.P. Wong, and M.Y.H. Low Bee colony optimization with local search for traveling salesman problem Int. J. Artif. Intell. Tools 19 2010 305 334
34. Colorni, A., Dorigo, M., Maniezzo, V., 1991. Distributed optimization by ant colonies. In: Proceedings of the first European conference on Artificial Life. Paris, France, pp. 134-142.
35. Consoli, S., Darby-Dowman, K., 2007. Combinatorial optimization and metaheuristics.
36. O. Cordon, F. Herrera, and T. Stützle A review on the ant colony optimization metaheuristic: basis, models and new trends Mathware Soft Comput. 9 2002 141 175
37. L.-P. Ding, Y.-X. Feng, J.-R. Tan, and Y.-C. Gao A new multi-objective ant colony algorithm for solving the disassembly line balancing problem Int. J. Adv. Manuf. Technol. 48 2010 761 771
38. A.V. Donati, R. Montemanni, N. Casagrande, A.E. Rizzoli, and L.M. Gambardella Time dependent vehicle routing problem with a multi ant colony system Eur. J. Oper. Res. 185 2008 1174 1191
39. M. Dorigo, and L.M. Gambardella Ant colonies for the traveling salesman problem BioSystems 43 1997 73 81
40. M. Dorigo, and L.M. Gambardella Ant colony system: a cooperative learning approach to the traveling salesman problem IEEE Trans. Evol. Comput. 1 1997 53 66
41. M. Dorigo, V. Maniezzo, and A. Colorni Ant system: optimization by a colony of cooperating agents IEEE Trans. Syst., Man Cybern. Part B: Cybern. 26 1996 29 41
42. T. Dyllick, and K. Hockerts Beyond the business case for corporate sustainability Bus. Strateg. Environ. 11 2002 130 141
43. G. Easwaran, and H. Üster A closed-loop supply chain network design problem with integrated forward and reverse channel decisions IIE Transactions 42 2010 779 792
44. Eberhart, R., Kennedy, J., 1995. A new optimizer using particle swarm theory (MHS'95). In: Proceedings of the Sixth IEEE International Symposium on Micro Machine and Human Science, pp. 39-43.
45. T. Efendigil, S. Önüt, and E. Kongar A holistic approach for selecting a third-party reverse logistics provider in the presence of vagueness Comput. Ind. Eng. 54 2008 269 287
46. B. Eksioglu, A.V. Vural, and A. Reisman The vehicle routing problem: A taxonomic review Comput. Ind. Eng. 57 2009 1472 1483
47. J. Elkington Partnerships from cannibals with forks: The triple bottom line of 21st-century business Environ. Qual. Manag. 8 1998 37 51
48. D. Favaretto, E. Moretti, and P. Pellegrini Ant colony system for a VRP with multiple time windows and multiple visits J. Interdiscip. Math. 10 2007 263 284
49. M. Fleischmann, J.M. Bloemhof-Ruwaard, R. Dekker, E. van der Laan, J.A.E.E. van Nunen, and L.N. Van Wassenhove Quantitative models for reverse logistics: a review Eur. J. Oper. Res. 103 1997 1 17
50. G. Fuellerer, K.F. Doerner, R.F. Hartl, and M. Iori Ant colony optimization for the two-dimensional loading vehicle routing problem Comput. Oper. Res. 36 2009 655 673
51. Y. Gajpal, and P. Abad An ant colony system (ACS) for vehicle routing problem with simultaneous delivery and pickup Comput. Oper. Res. 36 2009 3215 3223
52. Y. Gajpal, and P.L. Abad Multi-ant colony system (MACS) for a vehicle routing problem with backhauls Eur. J. Oper. Res. 196 2009 102 117
53. Y. Gajpal, and C. Rajendran An ant-colony optimization algorithm for minimizing the completion-time variance of jobs in flowshops Int. J. Prod. Econ. 101 2006 259 272
54. A.H. Gandomi, and A.H. Alavi Krill herd: a new bio-inspired optimization algorithm Commun. Nonlinear Sci. Numer. Simul. 17 2012 4831 4845
55. F.J.M. Garcia, and J.A.M. Perez Jumping frogs optimization: a new swarm method for discrete optimization Documentos de Trabajo del DEIOC 2008
56. F. Glover, and G.A. Kochenberger Handbook of Metaheuristics 2003 Springer New York
57. F.P. Goksal, I. Karaoglan, and F. Altiparmak A hybrid discrete particle swarm optimization for vehicle routing problem with simultaneous pickup and delivery Comput. Ind. Eng. 65 2013 39 53
58. W. Gong, D. Li, X. Liu, J. Yue, and Z. Fu Improved two-grade delayed particle swarm optimisation (TGDPSO) for inventory facility location for perishable food distribution centres in Beijing N. Z. J. Agric. Res. 50 2007 771 779
59. X.G. Gong, R.B. Xiao, and T.Y. Yu Modeling and simulation of ant colony's labor division with constraints for task allocation of resilient supply chains Int. J. Artif. Intell. Tools 21 2012 1240014
60. Y.J. Gong, J. Zhang, O. Liu, R.Z. Huang, H.S.H. Chung, and Y.H. Shi Optimizing the vehicle routing problem with time windows: a discrete particle swarm optimization approach IEEE Trans. Syst., Man, Cybern. Part C: Appl. Rev. 42 2012 254 267
61. Y. Hani, L. Amodeo, F. Yalaoui, and H. Chen Ant colony optimization for solving an industrial layout problem Eur. J. Oper. Res. 183 2007 633 642
62. Havens, T.C., Spain, C.J., Salmon, N.G., Keller, J.M., 2008. Roach infestation optimization. In: Proceedings of the IEEE Swarm Intelligence Symposium (SIS 2008), pp. 1-7.
63. A.A. Hervani, M.M. Helms, and J. Sarkis Performance measurement for green supply chain management Benchmarking 12 2005 330 353
64. J.H. Holland Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence 1975 U Michigan Press Oxford, England
65. T.J. Hu, and W.K. Cheng Modeling of vehicle routing problems with backhauls of reverse logistics and ant colony algorithm J. Transp. Syst. Eng. Inf. Technol. 10 2010 110 114
66. S.-H. Huang, and P.-C. Lin A modified ant colony optimization algorithm for multi-item inventory routing problems with demand uncertainty Transp. Res. Part E: Logist. Transp. Rev. 46 2010 598 611
67. R. Jeanne The evolution of the organization of work in social insects Monit. Zool. Ital. 20 1986 119 133
68. D.F. Jones, S.K. Mirrazavi, and M. Tamiz Multi-objective meta-heuristics: an overview of the current state-of-the-art Eur. J. Oper. Res. 137 2002 1 9
69. R.S. Kadadevaramath, J.C.H. Chen, B. Latha Shankar, and K. Rameshkumar Application of particle swarm intelligence algorithms in supply chain network architecture optimization Expert Syst. Appl. 39 2012 10160 10176
70. C.B. Kalayci, and S.M. Gupta Ant colony optimization for sequence-dependent disassembly line balancing problem J. Manuf. Technol. Manag. 24 2013 413 427
71. C.B. Kalayci, and S.M. Gupta Artificial bee colony algorithm for solving sequence-dependent disassembly line balancing problem Expert Syst. Appl. 40 2013 7231 7241
72. G. Kannan, A. Noorul Haq, and M. Devika Analysis of closed loop supply chain using genetic algorithm and particle swarm optimisation Int. J. Prod. Res. 47 2009 1175 1200
73. K. Kanthavel, P.S.S. Prasad, and K.P. Vignesh Optimization of vehicle routing problem with simultaneous delivery and pickup using nested particle swarm optimization Eur. J. Sci. Res. 73 2012 331 337
74. Karaboga, D., 2005. An idea based on honey bee swarm for numerical optimization.
75. N. Karadimas, N. Doukas, M. Kolokathi, and G. Defteraiou Routing optimization heuristic algorithms for urban solid waste transportation management WSEAS Trans. Comput. 7 2008 2022 2031
76. N.V. Karadimas, K. Papatzelou, and V.G. Loumos Optimal solid waste collection routes identified by the ant colony system algorithm WSEAS Trans. Comput. 25 2007 139 147
77. J.-P. Kenné, P. Dejax, and A. Gharbi Production planning of a hybrid manufacturing-remanufacturing system under uncertainty within a closed-loop supply chain Int. J. Prod. Econ. 135 2012 81 93
78. Kennedy, J., Eberhart, R., 1995. Particle swarm optimization. In: Proceedings of IEEE International Conference on Neural Networks. Perth, Australia, pp. 1942-1948.
79. H.J. Ko, and G.W. Evans A genetic algorithm-based heuristic for the dynamic integrated forward/reverse logistics network for 3PLs Comput. Oper. Res. 34 2007 346 366
80. Krishnan and, K., Ghose, D., 2005. Detection of multiple source locations using a glow-worm metaphor with applications to collective robotics. In: Proceedings of the IEEE Swarm Intelligence Symposium, pp. 84-91.
81. S. Kumanan, S. Prasanna Venkatesan, and J. Prasanna Kumar Optimisation of supply chain logistics network using random search techniques Int. J. Logist. Syst. Manag. 3 2007 252 266
82. S.K. Kumar, M.K. Tiwari, and R.F. Babiceanu Minimisation of supply chain cost with embedded risk using computational intelligence approaches Int. J. Prod. Res. 48 2009 3717 3739
83. V. Kumar, F.W. Liou, S.N. Balakrishnan, and V. Kumar Economical impact of RFID implementation in remanufacturing: a Chaos-based Interactive Artificial Bee Colony approach J. Intell. Manuf. 2013 1 16
84. G. Laporte The vehicle routing problem: An overview of exact and approximate algorithms Eur. J. Oper. Res. 59 1992 345 358
85. B. Latha Shankar, S. Basavarajappa, R.S. Kadadevaramath, and J.C.H. Chen A bi-objective optimization of supply chain design and distribution operations using non-dominated sorting algorithm: a case study Expert Syst Appl. 40 2013 5730 5739
86. C.-Y. Lee, Z.-J. Lee, S.-W. Lin, and K.-C. Ying An enhanced ant colony optimization (EACO) applied to capacitated vehicle routing problem Appl. Intell. 32 2010 88 95
87. C.K.M. Lee, and J.S.L. Lam Managing reverse logistics to enhance sustainability of industrial marketing Ind. Market. Manag. 41 2012 589 598
88. S. Li, and Y. Rong The research of online price quotation for the automobile parts exchange programme Int. J. Comput. Integr.Manuf. 22 2009 245 256
89. X.-l. Li, F. Lu, G.-h. Tian, and J.-x. QIAN Applications of artificial fish school algorithm in combinatorial optimization problems J. Shandong Univ. (Eng. Sci.) 34 2004 64 67
90. X. Li, and M. Yin A discrete artificial bee colony algorithm with composite mutation strategies for permutation flow shop scheduling problem Sci. Iran. 19 2012 1921 1935
91. C.-J. Liao, Y.-L. Tsai, and C.-W. Chao An ant colony optimization algorithm for setup coordination in a two-stage production system Appl. Soft Comput. 11 2011 4521 4529
92. B.M.T. Lin, C.Y. Lu, S.J. Shyu, and C.Y. Tsai Development of new features of ant colony optimization for flowshop scheduling Int. J. Prod. Econ. 112 2008 742 755
93. C.-W. Lin, and Y.-L. Chen Optimal green facility planning-implementation of organic rankine cycle system for factory waste heat recovery Int. J. Environ., Earth Sci. Eng 2013
94. C. Lin, K.L. Choy, G.T.S. Ho, S.H. Chung, and H.Y. Lam Survey of green vehicle routing problem: past and future trends Expert Syst. Appl 2013
95. X.-j. Liu, H. Yi, and Z.-h. Ni Application of ant colony optimization algorithm in process planning optimization J. Intell. Manuf. 24 2013 1 13
96. X. Liu, G. Peng, X. Liu, and Y. Hou Disassembly sequence planning approach for product virtual maintenance based on improved max-min ant system Int. J. Adv. Manuf. Technol. 59 2012 829 839
97. Y.-F. Liu, and S.-Y. Liu A hybrid discrete artificial bee colony algorithm for permutation flowshop scheduling problem Appl. Soft Comput. 13 2013 1459 1463
98. X. Lu, and Y. Zhou A novel Global Convergence Algorithm: Bee Collecting Pollen Algorithm, Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence 2008 Springer Berlin Heidelberg 518 525
99. Lucic, P., Teodorovic, D., 2002. Transportation modeling: an artificial life approach (ICTAI 2002). In: Proceedings of the 14th IEEE International Conference on Tools with Artificial Intelligence, pp. 216-223.
100. H. Lv, and C. Lu An assembly sequence planning approach with a discrete particle swarm optimization algorithm Int. J. Adv. Manuf. Technol. 50 2010 761 770
101. B. Mahadevan, D.F. Pyke, and M. Fleischmann Periodic review, push inventory policies for remanufacturing Eur. J. Oper. Res. 151 2003 536 551
102. Y. Marinakis, M. Marinaki, and G. Dounias Honey Bees Mating Optimization algorithm for large scale vehicle routing problems Nat. Comput. 9 2010 5 27
103. E.L. Marsillac Environmental impacts on reverse logistics and green supply chains: similarities and integration Int. J. Logist. Syst. Manag. 4 2008 411 422
104. E. Mastrocinque, B. Yuce, A. Lambiase, and M.S. Packianather A multi-objective optimisation for supply chain network using the bees algorithm Int. J. Eng. Bus. Manag. 5 2013 1 11
105. P. Mayring Qualitative content analysis A Companion to Qualitative Research 2004 266 269
106. M.I. Mazhar, S. Kara, and H. Kaebernick Remaining life estimation of used components in consumer products: life cycle data analysis by Weibull and artificial neural networks J. Oper. Manag. 25 2007 1184 1193
107. S. Mazzeo, and I. Loiseau An ant colony algorithm for the capacitated vehicle routing Electron. Notes Discret. Math. 18 2004 181 186
108. S. McGovern, and S. Gupta Ant colony optimization for disassembly sequencing with multiple objectives Int. J. Adv. Manuf. Technol. 30 2006 481 496
109. S.M. McGovern, and S.M. Gupta Combinatorial optimization analysis of the unary NP-complete disassembly line balancing problem Int. J. Prod. Res. 45 2007 4485 4511
110. P.R. McMullen An ant colony optimization approach to addressing a JIT sequencing problem with multiple objectives Artif. Intell. Eng. 15 2001 309 317
111. J. Meredith Theory building through conceptual methods Int. J. Oper. Prod. Manag. 13 1993 3 11
112. H. Min, and W.P. Galle Green purchasing strategies: trends and implications Int. J. Purch. Mater. Manag. 33 1997 10 17
113. M. Mirabi Ant colony optimization technique for the sequence-dependent flowshop scheduling problem Int. J. Adv. Manuf. Technol. 55 2011 317 326
114. S. Mirjalili, S.M. Mirjalili, and A. Lewis Gray wolf optimizer Adv. Eng. Softw. 69 2014 46 61
115. B.F. Moghaddam, R. Ruiz, and S.J. Sadjadi Vehicle routing problem with uncertain demands: an advanced particle swarm algorithm Comput. Ind. Eng. 62 2012 306 317
116. L.A. Moncayo-Martínez, and D.Z. Zhang Multi-objective ant colony optimisation: a meta-heuristic approach to supply chain design Int. J. Prod. Econ. 131 2011 407 420
117. R. Montemanni, L.M. Gambardella, A.E. Rizzoli, and A.V. Donati Ant colony system for a dynamic vehicle routing problem J. Comb. Optim. 10 2005 327 343
118. A. Mucherino, and O. Seref Monkey Search: A Novel Metaheuristic Search for Global Optimization, Data Mining, Systems Analysis and Optimization in Biomedicine 2007 American Institute of Physics New York 162 173
119. P.R.P.R.F. Murphy Green logistics strategies: an analysis of usage patterns Transp. J. (Am. Soc. Transp. Logist. Inc.) 40 2000 5 16
120. R. Musa, J.-P. Arnaout, and H. Jung Ant colony optimization algorithm to solve for the transportation problem of cross-docking network Comput. Ind. Eng. 59 2010 85 92
121. A. Mutha, and S. Pokharel Strategic network design for reverse logistics and remanufacturing using new and old product modules Comput. Ind. Eng. 56 2009 334 346
122. A. Noorul Haq, and G. Kannan Effect of forecasting on the multi-echelon distribution inventory supply chain cost using neural network, genetic algorithm and particle swarm optimisation Int. J. Serv. Oper. Inf. 1 2006 1 22
123. L. Özbakir, A. Baykasoʇlu, and P. Tapkan Bees algorithm for generalized assignment problem Appl. Math. Comput. 215 2010 3782 3795
124. A. Pal, F.T.S. Chan, B. Mahanty, and M.K. Tiwari Aggregate procurement, production, and shipment planning decision problem for a three-echelon supply chain using swarm-based heuristics Int. J. Prod. Res. 49 2010 2873 2905
125. W.-T. Pan A new fruit fly optimization algorithm: taking the financial distress model as an example Knowl.-Based Syst. 26 2012 69 74
126. S. Pandey, and S. Kumar Enhanced artificial bee colony algorithm and it's application to traveling salesman problem HCTL Open Int. J. Technol. Innov. Res. 2 2013 137 146
127. K.M. Passino Bacterial foraging optimization Int. J. Swarm Intell. Res. (IJSIR) 1 2010 1 16
128. N. Pathak, and S.P. Tiwari Traveling salesman problem using bee colony with SPV Int. J. Soft Comput. Eng. 13 2012 18
129. Pham, D., Ghanbarzadeh, A., Koc, E., Otri, S., Rahim, S., Zaidi, M., 2006. The bees algorithm-a novel tool for complex optimisation problems. In: Proceedings of the 2nd Virtual International Conference on Intelligent Production Machines and Systems (IPROMS 2006), pp. 454-459.
130. P.C. Pinto, T.A. Runkler, and J.M. Sousa Wasp swarm algorithm for dynamic MAX-SAT problems, Adaptive and Natural Computing Algorithms 2007 Springer Berlin Heidelberg 350 357
131. M.S. Pishvaee, R.Z. Farahani, and W. Dullaert A memetic algorithm for bi-objective integrated forward/reverse logistics network design Comput. Oper. Res. 37 2010 1100 1112
132. A. Prakash, M.K. Tiwari, and R. Shankar Optimal job sequence determination and operation machine allocation in flexible manufacturing systems: an approach using adaptive hierarchical ant colony algorithm J. Intell. Manuf. 19 2008 161 173
133. C. Qi Application of improved discrete particle swarm optimization in logistics distribution routing problem Proc. Eng. 15 2011 3673 3677
134. Qu, X.H., Song, W.F., Ding, B.R., Zhao, H., 2011. Research On the Triangle Distribution Model Based on Third-Party Logistics Alliance, PART 3 ed, Changchun, pp. 1508-1512.
135. C. Rajendran, and H. Ziegler Ant-colony algorithms for permutation flowshop scheduling to minimize makespan/total flowtime of jobs Eur. J. Oper. Res. 155 2004 426 438
136. C. Rajendran, and H. Ziegler Two ant-colony algorithms for minimizing total flowtime in permutation flowshops Comput. Ind. Eng. 48 2005 789 797
137. R. Rajesh, S. Pugazhendhi, and K. Ganesh Genetic algorithm and particle swarm optimization for solving balanced allocation problem of third party logistics providers Int. J. Inf. Syst. Supply Chain Manag. (IJISSCM) 4 2011 24 44
138. E. Rashedi, H. Nezamabadi-pour, and S. Saryazdi GSA: a gravitational search algorithm Inf. Sci. 179 2009 2232 2248
139. E. Rashedi, H. Nezamabadi-pour, and S. Saryazdi BGSA: binary gravitational search algorithm Nat. Comput. 9 2010 727 745
140. Reynolds, C.W., 1987. Flocks, herds and schools: a distributed behavioral model. ACM SIGGRAPH Computer Graphics. ACM, pp. 25-34.
141. A.E. Rizzoli, R. Montemanni, E. Lucibello, and L.M. Gambardella Ant colony optimization for real-world vehicle routing problems Swarm Intell. 1 2007 135 151
142. D.S. Rogers, and R. Tibben-Lembke An examination Of reverse logistics practices J. Bus. Logist. 22 2001 129 148
143. Roth, M., 2005. Termite: A Swarm Intelligent Routing Algorithm for Mobile Wireless Ad-Hoc Networks.
144. L. Santos, J. Coutinho-Rodrigues, and J.R. Current An improved ant colony optimization based algorithm for the capacitated arc routing problem Transp. Res. Part B: Methodol. 44 2010 246 266
145. H. Sarhadi, and K. Ghoseiri An ant colony system approach for fuzzy traveling salesman problem with time windows Int. J. Adv. Manuf. Technol. 50 2010 1203 1215
146. Sbihi, A., Eglese, R., 2007. Combinatorial Optimization and Green Logistics. 4OR 5, pp. 99-116.
147. M. Šelmić, D. Teodorović, and K. Vukadinović Locating inspection facilities in traffic networks: an artificial intelligence approach Transp. Plan. Technol. 33 2010 481 493
148. S. Seuring, and M. Müller From a literature review to a conceptual framework for sustainable supply chain management J. Clean. Prod. 16 2008 1699 1710
149. B.L. Shankar, S. Basavarajappa, and R.S. Kadadevaramath Bi-objective optimization of distribution scheduling using MOPSO optimizer J. Model. Manag. 7 2012 304 327
150. X.H. Shi, Y.C. Liang, H.P. Lee, C. Lu, and Q. Wang Particle swarm optimization-based algorithms for TSP and generalized TSP Inf. Process. Lett. 103 2007 169 176
151. Y.J. Shi, F.W. Meng, and G.J. Shen A modified artificial bee colony algorithm for vehicle routing problems with time windows Inf. Technol. J. 11 2012 1490 1495
152. Shiqin, Y., Jianjun, J., Guangxing, Y., 2009. A dolphin partner optimization, In: IEEE WRI Global Congress on Intelligent Systems (GCIS'09), pp. 124-128.
153. C.A. Silva, J.M.C. Sousa, T.A. Runkler, and J.M.G. Sá da Costa Distributed supply chain management using ant colony optimization Eur. J. Oper. Res. 199 2009 349 358
154. A. Singh, and D. Narayan Augmentation of traveling salesman problem using Bee Colony Optimization Int. J. Innov. Technol. Explor. Eng 2012
155. T. Stützle, and H.H. Hoos Max-min ant system Future Gener. Comput. Syst. 16 2000 889 914
156. P. Subramanian, N. Ramkumar, T.T. Narendran, and K. Ganesh A technical note on Analysis of closed loop supply chain using genetic algorithm and particle swarm optimisation Int. J. Prod. Res. 50 2012 593 602
157. Y. Suzuki A new truck-routing approach for reducing fuel consumption and pollutants emission Transp. Res. Part D: Transp. Environ. 16 2011 73 77
158. W.Y. Szeto, Y. Wu, and S.C. Ho An artificial bee colony algorithm for the capacitated vehicle routing problem Eur. J. Oper. Res. 215 2011 126 135
159. V. T'Kindt, N. Monmarché, F. Tercinet, and D. Laügt An Ant Colony Optimization algorithm to solve a 2-machine bicriteria flowshop scheduling problem Eur. J. Oper. Res. 142 2002 250 257
160. A. Taleizadeh, S. Niaki, N. Shafii, R. Meibodi, and A. Jabbarzadeh A particle swarm optimization approach for constraint joint single buyer-single vendor inventory problem with changeable lead time and (r,Q) policy in supply chain Int. J. Adv. Manuf. Technol. 51 2010 1209 1223
161. P. Toth, and D. Vigo An overview of vehicle routing problems The vehicle routing problem 9 2002 1 26
162. M. Tripathi, S. Agrawal, M.K. Pandey, R. Shankar, and M.K. Tiwari Real world disassembly modeling and sequencing problem: Optimization by Algorithm of Self-Guided Ants (ASGA) Robot. Comput.-Integr. Manuf. 25 2009 483 496
163. S. Validi, A. Bhattacharya, and P.J. Byrne Integrated low-carbon distribution system for the demand side of a product distribution supply chain: a DoE-guided MOPSO optimiser-based solution approach Int. J. Prod. Res 2013
164. S.P. Venkatesan, and S. Kumanan A Multi-Objective Discrete Particle Swarm Optimisation Algorithm for supply chain network design Int. J. Logist. Syst. Manag. 11 2012 375 406
165. V. Vinay, and R. Sridharan Taguchi method for parameter design in ACO algorithm for distribution-allocation in a two-stage supply chain Int. J. Adv. Manuf. Technol. 64 2013 1333 1343
166. S.V. Walton, R.B. Handfield, and S.A. Melnyk The green supply chain: integrating suppliers into environmental management processes Int. J. Purch. Mater. Manag. 34 1998 2 11
167. H.S. Wang A two-phase ant colony algorithm for multi-echelon defective supply chain network design Eur. J. Oper. Res. 192 2009 243 252
168. J.F. Wang, J.H. Liu, and Y.F. Zhong A novel ant colony algorithm for assembly sequence planning Int. J. Adv. Manuf. Technol. 25 2005 1137 1143
169. X. Wang, X. Xie, and T.C.E. Cheng A modified artificial bee colony algorithm for order acceptance in two-machine flow shops Int. J. Prod. Econ. 141 2013 14 23
170. Y.-P. Wang Adaptive ant colony algorithm for the VRP solution of logistics distribution Res. J. Appl. Sci., Eng. Technol. 6 2013 807 811
171. Y. Wang, and J.H. Liu Chaotic particle swarm optimization for assembly sequence planning Robot. Computer-Integr. Manuf. 26 2010 212 222
172. L.-P. Wong, C.Y. Puan, M.Y.H. Low, Y.W. Wong, and C.S. Chong Bee colony optimisation algorithm with big valley landscape exploitation for job shop scheduling problems Int. J. Bio-Inspir. Comput. 2 2010 85 99
173. B. Yagmahan, and M.M. Yenisey Ant colony optimization for multi-objective flow shop scheduling problem Comput. Ind. Eng. 54 2008 411 420
174. B. Yagmahan, and M.M. Yenisey A multi-objective ant colony system algorithm for flow shop scheduling problem Expert Syst. Appl. 37 2010 1361 1368
175. X.-S. Yang Firefly Algorithm, Nature-inspired Metaheuristic Algorithms 2008 Luniver Press Bristol, UK
176. X.-S. Yang A New Metaheuristic Bat-Inspired Algorithm, Nature Inspired Co-operative Strategies For Optimization (NICSO 2010) 2010 Springer Berlin Heidelberg 65 74
177. Yang, X.-S., Deb, S., 2009. Cuckoo search via Lévy flights. (NaBIC 2009). In: IEEEWorld Congress on Nature and Biologically Inspired Computing, pp. 210-214.
178. B. Yao, P. Hu, M. Zhang, and S. Wang Artificial bee colony algorithm with scanning strategy for the periodic vehicle routing problem Simulation 89 2013 762 770
179. L. Ye, C. Ye, and Y.-F. Chuang Location set covering for waste resource recycling centers in Taiwan Resour., Conserv. Recycl. 55 2011 979 985
180. W.-C. Yeh Simplified swarm optimization in disassembly sequencing problems with learning effects Comput. Oper. Res. 39 2012 2168 2177
181. W.C. Yeh Optimization of the disassembly sequencing problem on the basis of Self-Adaptive Simplified Swarm Optimization IEEE Trans. Syst., Man Cybern., Part A: Syst. Hum., 42 2012 250 261
182. G.G. Yen, and B. Ivers Job shop scheduling optimization through multiple independent particle swarms Int. J. Intell. Comput. Cybern. 2 2009 5 33
183. K.-C. Ying, and C.-J. Liao An ant colony system for permutation flow-shop sequencing Comput. Oper. Res. 31 2004 791 801
184. B. Yu, Z.-Z. Yang, and B. Yao An improved ant colony optimization for vehicle routing problem Eur. J. Oper. Res. 196 2009 171 176
185. B. Yu, and Z.Z. Yang An ant colony optimization model: the period vehicle routing problem with time windows Transp. Res. Part E: Logist. Transp. Rev. 47 2011 166 181
186. L. Yun-Chia, and A.E. Smith An ant colony optimization algorithm for the redundancy allocation problem (RAP) IEEE Trans. Reliab. 53 2004 417 423
187. Q.S. Zhang, and K. Guo A discrete artificial bee colony algorithm for the reverse logistics location and routing problem Int. J. Inf. Technol. Decis. Making 0 2014 1 19
188. R. Zhang, S. Song, and C. Wu A hybrid artificial bee colony algorithm for the job shop scheduling problem Int. J. Prod. Econ. 141 2013 167 178
189. T. Zhang, W.-x. Tian, Y.-j. Zhang, and S.-x. Liu Improved ant colony system for VRPSPD with maximum distance constraint Syst. Eng. - Theory Pract. 28 2008 132 140
190. C. Zhen-Hua, C. Tzu-An, T. Chuang, and C. Cheng-Jui A supplier selection model for product design changes Int. J. Electron. Bus. Manag. 8 2010 20 30
191. R. Zhou, A.Y.C. Nee, and H.P. Lee Performance of an ant colony optimisation algorithm in dynamic job shop scheduling problems Int. J. Prod. Res. 47 2009 2903 2920
192. X.C. Zhou, Z.X. Zhao, K.J. Zhou, and C.H. He Remanufacturing closed-loop SUPPLY chain network design based on genetic particle swarm optimization algorithm J. Central South Univ. Technol. (English Edition) 19 2012 482 487
193. Z. Zhou, S. Cheng, and B. Hua Supply chain optimization of continuous process industries with sustainability considerations Comput. Chem. Eng. 24 2000 1151 1158
194. Q. Zhu, and J. Zhang Ant colony optimisation with elitist ant for sequencing problem in a mixed model assembly line Int. J. Prod. Res. 49 2010 4605 4626