Skip to main content

Advertisement

SpringerLink
Log in

Extended Genetic Algorithm for solving open-shop scheduling problem

  • Methodologies and Application
  • Published:
Soft Computing Aims and scope Submit manuscript

Abstract

Open-shop scheduling problem (OSSP) is a well-known topic with vast industrial applications which belongs to one of the most important issues in the field of engineering. OSSP is a kind of NP problems and has a wider solution space than other basic scheduling problems, i.e., Job-shop and flow-shop scheduling. Due to this fact, this problem has attracted many researchers over the past decades and numerous algorithms have been proposed for that. This paper investigates the effects of crossover and mutation operator selection in Genetic Algorithms (GA) for solving OSSP. The proposed algorithm, which is called EGA_OS, is evaluated and compared with other existing algorithms. Computational results show that selection of genetic operation type has a great influence on the quality of solutions, and the proposed algorithm could generate better solutions compared to other developed algorithms in terms of computational times and objective values.

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
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22

Similar content being viewed by others

References

  • Ahmdizar F, Hosseinabadi M (2012) A novel hybrid genetic algorithm for the open-shop scheduling problem. Int J Adv Manuf Technol 62:775–787

    Article  Google Scholar 

  • Alinaghian M, Amanipour H, Tirkolaee EB (2014) Enhancement of inventory management approaches in vehicle routing-cross docking problems. J Supply Chain Manag Syst 3(3):27–34

    Google Scholar 

  • Azadeh A, Goldansaz SM, Zahedi-Anaraki A (2016) Solving and optimizing a bi-objective open-shop scheduling problem by a modified genetic algorithm. Int J Adv Manuf Technol 85:1603–1613

    Article  Google Scholar 

  • Babaee Tirkolaee E, Alinaghian M, Bakhshi Sasi M, Seyyed Esfahani MM (2016) Solving a robust capacitated arc routing problem using a hybrid simulated annealing algorithm: a waste collection application. J Ind Eng Manag Stud 3(1):61–76

    Google Scholar 

  • Bai D, Tang L (2013) Open shop scheduling problem to minimize makespan with release dates. Appl Math Model 37:2008–2015

    Article  MathSciNet  MATH  Google Scholar 

  • Baia D, Zhang Z, Zhang Q (2016) Flexible open-shop scheduling problem to minimize makespan. Comput Oper Res 67:207–215

    Article  MathSciNet  MATH  Google Scholar 

  • Chen Y, Zhang A, Chen G, Dong J (2013) Approximation algorithms for parallel open-shop scheduling. Inf Process Lett 113:220–224

    Article  MathSciNet  MATH  Google Scholar 

  • Ciro GC, Dugardin F, Yalaoui F, Kelly R (2015) A fuzzy ant colony optimization to solve an open-shop scheduling problem with multi-skills resource constraints. In: 8th IFAC conference on manufacturing modelling, management and control MIM 2015, vol 48, pp 715–720

  • Ciro GC, Dugardin F, Yalaoui F, Kelly R (2016) A NSGA-II and NSGA-III comparison for solving an open-shop scheduling problem with resource constraints. In: 8th IFAC conference on manufacturing modelling, management and control MIM 2016, vol 49, pp 1272–1277

  • Colak S, Agarwal A (2005) Non-greedy heuristics and augmented neural networks for the open-shop scheduling problem. Naval Res Logist 52:631–644

    Article  MathSciNet  MATH  Google Scholar 

  • Deb K, Jain H (2014) An evolutionary many-objective optimization algorithm using reference-point based nondominated sorting approach. IEEE Trans Evol Comput 18:602–622

    Article  Google Scholar 

  • Fang H-L, Ross P, Corne D (1994) A promising hybrid GA/heuristic approach for open-shop scheduling problems. In: Proceedings of the 11th European conference on artificial intelligence, pp 590–594

  • Farahabadi AB, Hosseinabadi AR (2013) Present a new hybrid algorithm scheduling flexible manufacturing system consideration cost maintenance. Int J Sci Eng Res 4(9):1870–1875

    Google Scholar 

  • Goldansaz SM, Jolai F, ZahediAnaraki AH (2013) A hybrid imperialist competitive algorithm for minimizing makespan in a multi-processor open-shop. Appl Math Model 37:9603–9616

    Article  MathSciNet  MATH  Google Scholar 

  • Gonzalez T, Sahni S (1976) Open-shop scheduling to minimize finish time. J Assoc Comput Mach 23:665–679

    Article  MathSciNet  MATH  Google Scholar 

  • Graham RL, Lawler EL, Lenstra JK, Kan AHG (1979) Optimization and approximation in deterministic machine scheduling: a survey. Ann Discrete Math 5:287–326

    Article  MathSciNet  MATH  Google Scholar 

  • Harmanani HM, Ghosn SB (2016) An efficient method for the open-shop scheduling problem using simulated annealing. Inf Technol New Gener Adv Intell Syst Comput 448:1183–1193

    Google Scholar 

  • Hosseinabadi AR, Yazdanpanah M, Rostami AS (2012) A new search algorithm for solving symmetric traveling salesman problem based on gravity. World Appl Sci J 16(10):1387–1392

    Google Scholar 

  • Hosseinabadi AR, Farahabadi AB, Rostami MS, Lateran AF (2013) Presentation of a new and beneficial method through problem solving timing of open-shop by random algorithm gravitational emulation local search. Int J Comput Sci Issues 10(1, No 2):745–752

    Google Scholar 

  • Hosseinabadi AR, Kardgar M, Shojafar M, Shamshirband S, Abraham A (2014) GELS-GA: hybrid metaheuristic algorithm for solving multiple travelling salesman problem. In: 14th IEEE ISDA, pp 76–81

  • Hosseinabadi AR, Siar H, Shamshirband S, Shojafar M, Nizam MH, Nasir M (2015) Using the gravitational emulation local search algorithm to solve the multi-objective flexible dynamic job shop scheduling problem in Small and Medium Enterprises. Ann Oper Res 229(1):451–474

    Article  MathSciNet  MATH  Google Scholar 

  • Hosseinabadi AR, Vahidi J, Balas VE, Mirkamali SS (2016a) OVRP_GELS: solving open vehicle routing problem using the gravitational emulation local search algorithm. Neural Comput Appl 29(10):955–968

    Article  Google Scholar 

  • Hosseinabadi AR, Kardgar M, Shojafar M, Shamshirband Sh, Abraham A (2016b) Gravitational search algorithm to solve open vehicle routing problem. In: 6th international conference on innovations in bio-inspired computing and applications (IBICA 2015). Chapter advances in intelligent systems and computing, Kochi, India. Springer, pp 93–103

  • Hosseinabadi AR, Alavipour F, Shamshirbnd Sh, Balas VE (2017a) A novel meta-heuristic combinatory method for solving capacitated vehicle location-routing problem with hard time windows. Springer International Publishing Switzerland (2017) Transportation systems, advances in intelligent systems and computing, vol 454. Springer, China, pp 707–728

  • Hosseinabadi AR, Rostami NSH, Kardgar M, Mirkamali SS, Abraham A (2017b) A new efficient approach for solving the capacitated vehicle routing problem using the gravitational emulation local search algorithm. Appl Math Model 49:663–679

    Article  MathSciNet  Google Scholar 

  • Karagöz S, Yıldız AR (2017) A comparison of recent metaheuristic algorithms for crashworthiness optimisation of vehicle thin-walled tubes considering sheet metal forming effects. Int J Veh Des 73:179–188

    Article  Google Scholar 

  • Khuri S, Miryala SR (1999) Genetic algorithms for solving open-shop scheduling problems. In: Proceedings of the 9th Portuguese conference on artificial intelligence. Lecture Notes in Computer Science, pp 357–368

  • Koulamas C, Kyparisis GJ (2015) The three-machine proportionate Open-shop and mixed shop minimum makespan problems. Eur J Oper Res 243:70–74

    Article  MathSciNet  MATH  Google Scholar 

  • Lawler EL, Lenstra JK, Rinnooy Kan AHG, Shmoys DB (1993) Sequencing and scheduling: algorithms and complexity. In: Graves SC, Rinnooy Kan AHG, Zipkin PH (eds) Handbook in operations research and management science, logistics of production and inventory, 4th edn. North-Holland, Amsterdam, pp 445–522

    Chapter  Google Scholar 

  • Low C, Yeh Y (2009) Genetic algorithm-based heuristics for an open-shop scheduling problem with setup, processing, and removal times separated. Robot Comput Integr Manuf 25:314–322

    Article  Google Scholar 

  • Mirmohammadi SH, Babaee Tirkolaee E, Goli A, Dehnavi-Arani S (2017) The periodic green vehicle routing problem with considering of time-dependent urban traffic and time windows. Iran Univ Sci Technol 7(1):143–156

    Google Scholar 

  • Noori-Darvish S, Tavakkoli-Moghaddam R (2011) Solving a bi-objective open-shop scheduling problem with fuzzy parameters. J Appl Oper Res 3:59–74

    Google Scholar 

  • Pinedo M (1995) Scheduling: theory algorithms and systems. Prentice-Hall, Englewood Cliffs

    MATH  Google Scholar 

  • Prins C (2000) Competitive genetic algorithms for the open-shop scheduling problem. Math Methods Oper Res 52:389–411

    Article  MathSciNet  MATH  Google Scholar 

  • Rostami AS, Mohanna F, Keshavarz H, Hosseinabadi AR (2015) Solving multiple traveling salesman problem using the gravitational emulation local search algorithm. Appl Math Inf Sci 9(2):699–709

    MathSciNet  Google Scholar 

  • Shamshirband S, Shojafar M, Hosseinabadi AR, Kardgar M, Nizam MH, Nasir M, Ahmad R (2015a) OSGA: genetic-based open-shop scheduling with consideration of machine maintenance in small and medium enterprises. Ann Oper Res 229(1):743–758

    Article  MathSciNet  MATH  Google Scholar 

  • Shamshirband S, Shojafar M, Hosseinabadi AR, Abraham A (2015b) OVRP_ICA: an imperialist-based optimization algorithm for the open vehicle routing problem. In: International conference on hybrid artificial intelligence systems (HAIS), Chapter Springer LNCS, vol 9121, pp 221–233

  • Shojafar M, Kardgar M, Hosseinabadi AR, Shamshirband Sh, Abraham A (2016) TETS: a genetic-based scheduler in cloud computing to decrease energy and makespan. In: The 15th international conference on hybrid intelligent systems (HIS 2015), Chapter advances in intelligent systems and computing, vol 420. Seoul, South Korea. Springer, pp 103–115

  • Taillard E (1993) Benchmarks for basic scheduling problems. Eur J Oper Res 64:278–285

    Article  MATH  Google Scholar 

  • Talbi, El-Ghazali (2009) Metaheuristics: from design to impelementation. Wiley, Hoboken. ISBN: 978-0-470-27858-1, 1–624

  • Tavakkolai H, Hosseinabadi AR, Yadollahi M, Mohammadpour T (2015) Using gravitational search algorithm for in advance reservation of resources in solving the scheduling problem of works in workflow workshop environment. Indian J Sci Technol 8(11):1–16

    Article  Google Scholar 

  • Tellache NEH, Boudhar M (2017) Open shop scheduling problems with conflict graphs. Discrete Appl Math 227:103–120

    Article  MathSciNet  MATH  Google Scholar 

  • Tirkolaee EB, Goli A, Bakhshi M, Mahdavi I (2017) Robust multi-trip vehicle routing problem of perishable products with intermediate depots and time windows. Numer Algebra Control Optim 7(4):417–433

    Article  MathSciNet  MATH  Google Scholar 

  • Tirkolaee EB, Alinaghian A, Hosseinabadi AAR, Sasi MB, Sangaiah AK (2018) An improved ant colony optimization for the multi-trip Capacitated Arc Routing Problem. Comput Electr Eng. ISSN 0045-7906. https://doi.org/10.1016/j.compeleceng.2018.01.040

  • Vasant P (2014) Handbook of research on artificial intelligence techniques and algorithms. IGI Global 1–796(ISBN13):9781466672581

    Google Scholar 

  • Vasant P, Wilhelm Weber G, Dieu VN (2016) Handbook of research modern optimization algorithms and applications in engineering and economics. IGI Global 1–960(ISBN13):9781466696440

    MATH  Google Scholar 

  • Yildiz AR (2012) A comparative study of population-based optimization algorithms for turning operations. Inf Sci 210:81–88

    Article  Google Scholar 

  • Yıldız AR, Ozturk N, Kaya N, Ozturk F (2007) Hybrid multi-objective shape design optimization using Taguchi’s method and genetic algorithm. Struct Multidiscip Optim 34:317–332

    Article  Google Scholar 

  • Zhang ZH, Bai D (2014) An extended study on an open-shop scheduling problem using the minimisation of the sum of quadratic completion times. Appl Math Comput 230:238–247

    MathSciNet  MATH  Google Scholar 

Download references

Acknowledgements

The authors are very thankful for the suggested comments of the Editor in Chief and reviewers to improve our paper.

Author information

Authors and Affiliations

  1. Young Researchers and Elite Club, Ayatollah Amoli Branch, Islamic Azad University, Amol, Iran

    Ali Asghar Rahmani Hosseinabadi

  2. Iran University of Science and Technology, Tehran, Iran

    Javad Vahidi

  3. Computer Department, Kavosh Institute of Higher Education, Mahmood Abad, Mazandaran, Iran

    Behzad Saemi

  4. School of Computing Science and Engineering, Vellore Institute of Technology (VIT), Vellore, 632014, India

    Arun Kumar Sangaiah

  5. Faculty of Computers and Information, Mansoura University, Mansoura, Egypt

    Mohamed Elhoseny

Authors
  1. Ali Asghar Rahmani Hosseinabadi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Javad Vahidi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Behzad Saemi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Arun Kumar Sangaiah
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Mohamed Elhoseny
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Arun Kumar Sangaiah.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Communicated by V. Loia.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rahmani Hosseinabadi, A.A., Vahidi, J., Saemi, B. et al. Extended Genetic Algorithm for solving open-shop scheduling problem. Soft Comput 23, 5099–5116 (2019). https://doi.org/10.1007/s00500-018-3177-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00500-018-3177-y

Keywords

Search

Navigation