A bi-objective fleet size and mix green inventory routing problem, model and solution method

Soft Computing

Volumn 23, Issue 4, 2019, Pages 1375-1391

  Alinaghian, Mehdi ^a   Zamani, Mohsen ^a  

^a ISFAHAN UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Fuel consumption; Multi objective optimization; NSGAII; Pollutant emissions; Quantum evolutionary algorithm; The fleet size and mix IRP

Indexed keywords

DECISION MAKING; ENVIRONMENTAL IMPACT; FUEL CONSUMPTION; GENETIC ALGORITHMS; HEURISTIC ALGORITHMS; MULTIOBJECTIVE OPTIMIZATION;

FLEET SIZE AND MIXES; HETEROGENEOUS FLEET; INVENTORY ROUTING PROBLEMS; META HEURISTIC ALGORITHM; NON-DOMINATED SORTING GENETIC ALGORITHM - II; NSGA-II; POLLUTANT EMISSION; QUANTUM EVOLUTIONARY ALGORITHMS;

FLEET OPERATIONS;

EID: 85031433058     PISSN: 14327643     EISSN: 14337479     Source Type: Journal    
DOI: 10.1007/s00500-017-2866-2     Document Type: Article

References (51)

1. Adulyasak Y, Cordeau J-F, Jans R (2013) Formulations and branch-and-cut algorithms for multivehicle production and inventory routing problems. INFORMS J Comput 26:103–120
2. Ahmadi Javid A, Azad N (2010) Incorporating location, routing and inventory decisions in supply chain network design. Transp Res Part E Logist Transp Rev 46:582–597
3. Alinaghian M, Ghazanfari M, Salamatbakhsh A, Norouzi N (2012) A new competitive approach on multi-objective periodic vehicle routing problem. Int J Appl Oper Res 1:33–41
4. Aydın N (2014) A genetic algorithm on inventory routing problem. EMAJ Emerg Mark J 3:59–66
5. Bell WJ, Dalberto LM, Fisher ML, Greenfield AJ, Jaikumar R, Kedia P et al (1983) Improving the distribution of industrial gases with an on-line computerized routing and scheduling optimizer. Interfaces 13:4–23
6. Bertazzi L, Bosco A, Guerriero F, Laganà D (2013) A stochastic inventory routing problem with stock-out. Transp Res Part C Emerg Technol 27:89–107
7. Campbell AM, Savelsbergh MW (2004) A decomposition approach for the inventory-routing problem. Transp Sci 38:488–502
8. Chrysochoou EC, Ziliaskopoulos AK, Lois A (2015) An exact algorithm for the stochastic inventory routing problem with transhipment. In: Transportation research board 94th annual meeting
9. Cohon JL (2013) Multiobjective programming and planning. Courier Corporation, North Chelmsford
10. Deb K (2014) Multi-objective optimization. In: Burke E, Kendall G (eds) Search methodologies. Springer, Boston, MA
11. Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6:182–197
12. Demir E, Bektaş T, Laporte G (2014) The bi-objective pollution-routing problem. Eur J Oper Res 232:464–478
13. Deng W, Zhao H, Liu J, Yan X, Li Y, Yin L et al (2015) An improved CACO algorithm based on adaptive method and multi-variant strategies. Soft Comput 19:701–713
14. Deng W, Zhao H, Zou L, Li G, Yang X, Wu D (2017a) A novel collaborative optimization algorithm in solving complex optimization problems. Soft Comput 21:4387–4398
15. Deng W, Zhao H, Yang X, Xiong J, Sun M, Li B (2017b) Study on an improved adaptive PSO algorithm for solving multi-objective gate assignment. Appl Soft Comput 59:288–302
16. Golden B, Assad A, Levy L, Gheysens F (1984) The fleet size and mix vehicle routing problem. Comput Oper Res 11:49–66
17. Gu B, Sun X, Sheng VS (2017) Structural minimax probability machine. IEEE Trans Neural Netw Learn Syst 28:1646–1656
18. Halim H, Moin N (2014) Solving inventory routing problem with backordering using Artificial Bee Colony. In: International conference on industrial engineering and engineering management (IEEM), 2014 IEEE, pp 913–917
19. Han K-H, Kim J-H (2002) Quantum-inspired evolutionary algorithm for a class of combinatorial optimization. IEEE Trans Evol Comput 6:580–593
20. Han K-H, Kim J-H (2004) Quantum-inspired evolutionary algorithms with a new termination criterion, Hε gate, and two-phase scheme. IEEE Trans Evol Comput 8:156–169
21. Huang S-H, Lin P-C (2010) A modified ant colony optimization algorithm for multi-item inventory routing problems with demand uncertainty. Transp Res Part E Logist Transp Rev 46:598–611
22. Jolai F, Amalnick MS, Alinaghian M, Shakhsi-Niaei M, Omrani H (2011) A hybrid memetic algorithm for maximizing the weighted number of just-in-time jobs on unrelated parallel machines. J Intell Manuf 22:247–261
23. Kaye P, Laflamme R, Mosca M (2007) An introduction to quantum computing. Oxford University Press, Oxford
24. Koç Ç, Bektaş T, Jabali O, Laporte G (2014) The fleet size and mix pollution-routing problem. Transp Res Part B Methodol 70:239–254
25. Kong Y, Zhang M, Ye D (2017) A belief propagation-based method for task allocation in open and dynamic cloud environments. Knowl Based Syst 115:123–132
26. Kopfer H (2013) Emissions minimization vehicle routing problem in dependence of different vehicle classes. In: Kreowski H-J, Scholz-Reiter B, Thoben K-D (eds) Dynamics in Logistics. Springer, Berlin, Heidelberg, pp 49–58
27. Kwon YJ, Choi YJ, Lee DH (2013) Heterogeneous fixed fleet vehicle routing considering carbon emission. Transp Res Part D Transp Environ 23:81–89
28. Lee HL, Seungjin W (2008) The whose, where and how of inventory control design. Supply Chain Manag Rev 12:22–29
29. Liu Q, Cai W, Shen J, Fu Z, Liu X, Linge N (2016) A speculative approach to spatial-temporal efficiency with multi-objective optimization in a heterogeneous cloud environment. Secur Commun Netw 9:4002–4012
30. Mavrotas G (2009) Effective implementation of the ε -constraint method in multi-objective mathematical programming problems. Appl Math Comput 213:455–465
31. Mirzapour Al-e-hashem SMJ, Rekik Y (2014) Multi-product multi-period Inventory Routing Problem with a transshipment option: a green approach. Int J Prod Econ 157:80–88
32. Moin N, Salhi S, Aziz N (2011) An efficient hybrid genetic algorithm for the multi-product multi-period inventory routing problem. Int J Prod Econ 133:334–343
33. Montgomery DC (2017) Design and analysis of experiments. Wiley
34. Niakan F, Rahimi M (2015) A multi-objective healthcare inventory routing problem; a fuzzy possibilistic approach. Transp Res Part E Logist Transp Rev 80:74–94
35. Platel MD, Schliebs S, Kasabov N (2007) A versatile quantum-inspired evolutionary algorithm. In: IEEE congress on evolutionary computation, 2007. CEC 2007, pp 423–430
36. Raa B, Aghezzaf E-H (2008) Designing distribution patterns for long-term inventory routing with constant demand rates. Int J Prod Econ 112:255–263
37. Rakke JG, Andersson H, Christiansen M, Desaulniers G (2014) A new formulation based on customer delivery patterns for a maritime inventory routing problem. Transp Sci 49:384–401
38. + -isomorphism method in social network based on graph similarity detection. Soft Comput. doi:10.1007/s00500-017-2513-y
39. Savelsbergh M, Song J-H (2007) Inventory routing with continuous moves. Comput Oper Res 34:1744–1763
40. Sbihi A, Eglese RW (2007) Combinatorial optimization and green logistics. 4OR Q J Oper Res 5:99–116
41. Schott JR (1995) Fault tolerant design using single and multicriteria genetic algorithm optimization, TIC Document1995
42. Shao S, Huang GQ (2014) A SHIP inventory routing problem with heterogeneous vehicles under order-up-to level policies. In: Proceedings of IIE annual conference, p 1106
43. Shen Z-JM, Coullard C, Daskin MS (2003) A joint location-inventory model. Transp Sci 37:40–55
44. Soysal M, Bloemhof-Ruwaard JM, Haijema R, van der Vorst JG (2015) Modeling an Inventory Routing Problem for perishable products with environmental considerations and demand uncertainty. Int J Prod Econ 164:118–133
45. Trudeau P, Dror M (1992) Stochastic inventory routing: route design with stockouts and route failures. Transp Sci 26:171–184
46. Xue Y, Jiang J, Zhao B, Ma T (2017) A self-adaptive artificial bee colony algorithm based on global best for global optimization. Soft Comput. doi:10.1007/s00500-017-2547-1
47. Yang P-C, Wee H-M (2002) A single-vendor and multiple-buyers production-inventory policy for a deteriorating item. Eur J Oper Res 143:570–581
48. Zhang G (2011) Quantum-inspired evolutionary algorithms: a survey and empirical study. J Heuristics 17:303–351
49. Zhang J, Wang W, Zhao Y, Cattani C (2012) Multiobjective quantum evolutionary algorithm for the vehicle routing problem with customer satisfaction. Math Probl Eng 2012:1–19
50. Zhou A, Qu B-Y, Li H, Zhao S-Z, Suganthan PN, Zhang Q (2011) Multiobjective evolutionary algorithms: a survey of the state of the art. Swarm Evol Comput 1:32–49
51. Zitzler E, Thiele L (1998) Multi-objective optimization using evolutionary algorithms—a comparative case study. In: International conference on parallel problem solving from nature. Springer, Berlin, Heidelberg, pp 292–301