Skip to main content

Advertisement

SpringerLink
Log in

A novel chaotic imperialist competitive algorithm for production and air transportation scheduling problems

  • Original Article
  • Published:
Neural Computing and Applications Aims and scope Submit manuscript

Abstract

Although production and transportation scheduling problems are of two essential issues in supply chain management, they are rarely integrated. In this paper, we study the problem of production and transportation scheduling to minimize total cost of supply chain. The problem is mathematically modeled. Moreover, a novel metaheuristic based on an imperialist competitive algorithm is developed for solving the problem. The proposed algorithm is enriched by a chaotic map and two new operators to avoid from local optima. To tune the parameters, Taguchi experimental design is applied. For evaluation of the proposed algorithm, it is compared with an available genetic algorithm. Finally, using numerical experiments, the outperformance of the proposed algorithm is shown in both solution quality and performance robustness.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

References

  1. Liu C-H (2011) Using genetic algorithms for the coordinated scheduling problem of a batching machine and two-stage transportation. Appl Math Comput 217:10095–10104

    Article  MathSciNet  MATH  Google Scholar 

  2. Lee YH, Jeong CS, Moon C (2002) Advanced planning and scheduling with outsourcing in manufacturing supply chain. Comput Ind Eng 43(1–2):351–374

    Article  Google Scholar 

  3. Monkman SK, Morrice DJ, Bard JF (2008) A production scheduling heuristic for an electronics manufacturer with sequence-dependent setup costs. Eur J Oper Res 187(3):1100–1114

    Article  MATH  Google Scholar 

  4. Cesaret B, Oğuz C, Salman FS (2012) A tabu search algorithm for order acceptance and scheduling. Comput Oper Res 39(6):1197–1205

    Article  Google Scholar 

  5. Wilson MC (2007) The impact of transportation disruptions on supply chain performance. Transp Res Part E Logist Transp Rev 43(4):295–320

    Article  Google Scholar 

  6. Tsao Y-C, Lu J-C (2012) A supply chain network design considering transportation cost discounts. Transp Res Part E Logist Transp Rev 48(2):401–414

    Article  Google Scholar 

  7. Chan FT, Zhang T (2011) The impact of collaborative transportation management on supply chain performance: a simulation approach. Expert Syst Appl 38(3):2319–2329

    Article  MathSciNet  Google Scholar 

  8. Scholz-Reiter B, Frazzon EM, Makuschewitz T (2010) Integrating manufacturing and logistic systems along global supply chains. CIRP J Manuf Sci Technol 2(3):216–223

    Article  Google Scholar 

  9. Garcia J, Lozano S, Canca D (2004) Coordinated scheduling of production and delivery from multiple plants. Robot Comput Integr Manuf 20(3):191–198

    Article  Google Scholar 

  10. Lee C-Y, Chen Z-L (2001) Machine scheduling with transportation considerations. J Sched 4(1):3–24

    Article  MathSciNet  MATH  Google Scholar 

  11. Pundoor G, Chen Z-L (2005) Scheduling a production–distribution system to optimize the tradeoff between delivery tardiness and distribution cost. Nav Res Logist 52(6):571–589

    Article  MathSciNet  MATH  Google Scholar 

  12. Chen Z-L, Vairaktarakis GL (2005) Integrated scheduling of production and distribution operations. Manag Sci 51(4):614–628

    Article  MATH  Google Scholar 

  13. Selvarajah E, Steiner G (2006) Batch scheduling in a two-level supply chain—a focus on the supplier. Eur J Oper Res 173(1):226–240

    Article  MathSciNet  MATH  Google Scholar 

  14. Vega H (2008) Air cargo, trade and transportation costs of perishables and exotics from South America. J Air Transp Manag 14(6):324–328

    Article  Google Scholar 

  15. Li K, Ganesan VK, Sivakumar AI (2006) Scheduling of single stage assembly with air transportation in a consumer electronic supply chain. Comput Ind Eng 51(2):264–278

    Article  Google Scholar 

  16. Li K, Sivakumar AI, Ganesan VK (2008) Complexities and algorithms for synchronized scheduling of parallel machine assembly and air transportation. Eur J Oper Res 187:442–455

    Article  MathSciNet  MATH  Google Scholar 

  17. Zandieh M, Molla-Alizadeh-Zavardehi S (2009) Synchronizing production and air transportation scheduling using mathematical programming models. J Comput Appl Math 230:546–558

    Article  MathSciNet  MATH  Google Scholar 

  18. Rostamian Delavar M, Hajiaghaei-Keshteli M, Molla-Alizadeh-Zavardehi S (2010) Genetic algorithms for coordinated scheduling of production and air transportation. Expert Syst Appl 37:8255–8266

    Article  Google Scholar 

  19. Naderi B, Roshanaei V (2014) No-idle time scheduling of open shops: modeling and metaheuristic solution methods. Int J Supply Oper Manag 1(1):54–68

    Google Scholar 

  20. Zegordi SH, Beheshti Nia MA (2009) A multi-population genetic algorithm for transportation scheduling. Transp Res Part E 946–959:946–959

    Article  Google Scholar 

  21. Zegordi S, Kamal Abadi I, Beheshti Nia M (2010) A novel genetic algorithm for solving production and transportation scheduling in a two-stage supply chain. Comput Ind Eng 58(3):373–381

    Article  Google Scholar 

  22. Atashpaz-Gargari E, Lucas C (2007) Imperialist competitive algorithm: an algorithm for optimization inspired by imperialistic competition. In: Evolutionary computation, Singapore

  23. Talatahari S, Farahmand Azar B, Sheikholeslami R, Gandomi AH (2012) Imperialist competitive algorithm combined with chaos for global optimization. Commun Nonlinear Sci Numer Simul 17:1312–1319

    Article  MathSciNet  MATH  Google Scholar 

  24. Duan H, Xu C, Liu S, Shao S (2010) Template matching using chaotic imperialist competitive algorithm. Pattern Recogn Lett 31:1868–1875

    Article  Google Scholar 

  25. Nazari-Shirkouhi S, Eivazy H, Ghodsi R, Rezaie K, Atashpaz-Gargari E (2010) Solving the integrated product mix-outsourcing problem using the imperialist competitive algorithm. Expert Syst Appl 37:7615–7626

    Article  Google Scholar 

  26. Chen G, Dong X (1998) From chaos to order: methodologies, perspectives and applications. World Scientific, Singapore

    MATH  Google Scholar 

  27. Lu H-j, Zhang H-m, MA L-h (2006) A new optimization algorithm based on chaos. Sci J Zhejiang Univ 539–542

  28. Gao L, Liu X (2009) A resilient particle swarm optimization algorithm based on chaos and appling it to optimize the fermentation process. Int J Inf Syst Sci 5(3):380–391

    Google Scholar 

  29. Bahrami H, Faez K, Abdechiri M (2010) Imperialist competitive algorithm using chaos theory for optimization. In: 12th International conference on computer modelling and simulation

  30. Naderi B, Zandieh M, Ghoshe Balagh AK, Roshanaei V (2009) An improved simulated annealing for hybrid flow shops with sequence-dependent setup and transportation times to minimize total completion time and total tardiness. Expert Syst Appl 36:9625–9633

    Article  Google Scholar 

  31. Vignaux GA, Michalewicz Z (1991) A genetic algorithm for the linear transportation problem. IEEE Trans Syst Man Cybern 21:445–452

    Article  MathSciNet  MATH  Google Scholar 

  32. Park H-H, Grings A, dos Santosc MV, Soares AS (2008) Parallel hybrid evolutionary computation: Automatic tuning of parameters for parallel gene expression programming. Appl Math Comput 201(2):108–120

    Article  MathSciNet  MATH  Google Scholar 

  33. Ries J, Beullens P, Salt D (2012) Instance-specific multi-objective parameter tuning based on fuzzy logic. Eur J Oper Res 218(2):305–315

    Article  MATH  Google Scholar 

  34. Tiwari M, Raghavendra N, Agrawal S, Goyal S (2010) A hybrid Taguchi–immune approach to optimize an integrated supply chain design problem with multiple shipping. Eur J Oper Res 203(1):95–106

    Article  MATH  Google Scholar 

  35. Subbaraj P, Rengaraj R, Salivahanan S (2011) Enhancement of Self-adaptive real-coded genetic algorithm using Taguchi method for Economic dispatch problem. Appl Soft Comput 11(1):83–92

    Article  Google Scholar 

  36. Tang C-Y, Wu Y-L, Peng C-C (2012) Fundamental matrix estimation by multiobjective genetic algorithm with Taguchi’s method. Appl Soft Comput 12(1):553–558

    Article  Google Scholar 

  37. Taguchi G (1986) Introduction to quality engineering. White Plains, Asian Productivity Organization/UNIPUB

  38. Phadke M (1989) Quality engineering using robust design. Prentice-Hall, Englewood Cliffs

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran

    A. Mortazavi, A. Arshadi Khamseh & B. Naderi

Authors
  1. A. Mortazavi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. Arshadi Khamseh
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. B. Naderi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to B. Naderi.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mortazavi, A., Khamseh, A.A. & Naderi, B. A novel chaotic imperialist competitive algorithm for production and air transportation scheduling problems. Neural Comput & Applic 26, 1709–1723 (2015). https://doi.org/10.1007/s00521-015-1828-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00521-015-1828-9

Keywords

Search

Navigation