Nothing Special   »   [go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

A set of efficient heuristics for a home healthcare problem

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

Abstract

Nowadays, the aging population and the little availability of informal care are two of the several factors leading to an increased need for assisted living support. Hence, home healthcare (HHC) operations including a set of nurses and patients have been developed recently by both academia and health practitioners to consider elderlies’ preferences willing to receive their cares at their homes instead of hospitals or retirement homes. Commonly, different services, e.g., nursing, physiotherapy, housekeeping and cleaning, for an HHC system are performed by nurses at patients’ homes after scheduling and routing the nurses by decision makers. Due to the difficulty of the problem, recent studies show a great deal of interest in applying various metaheuristics and heuristics to solve this problem. To alleviate the drawbacks of previous works and make HHC more practical, this paper develops not only a new mathematical formulation considering new suppositions in this research area but also a lower bound based on Lagrangian relaxation theory has been employed. As such, three new heuristics and a hybrid constructive metaheuristic are utilized in this study to solve the proposed model. Finally, the performance of the proposed algorithms is validated by the developed lower bound and also analyzed by different criteria and also the efficiency of developed formulation is probed through some sensitivity analyses.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

Notes

  1. https://www.statista.com/statistics/185249/persons-employed-in-home-health-care-services-in-the-us-since-2000/.

References

  1. Fikar C, Hirsch P (2017) Home health care routeing and scheduling: a review. Comput Oper Res 77:86–95

    Article  MathSciNet  MATH  Google Scholar 

  2. Shi Y, Boudouh T, Grunder O (2017) A hybrid genetic algorithm for a home health care routeing problem with time window and fuzzy demand. Expert Syst Appl 72:160–176

    Article  Google Scholar 

  3. Lin CC, Hung LP, Liu WY, Tsai MC (2018) Jointly rostering, routeing, and re-rostering for home health care services: a harmony search approach with genetic, saturation, inheritance, and immigrant schemes. Comput Ind Eng 115:151–166

    Article  Google Scholar 

  4. Cappanera P, Scutellà MG, Nervi F, Galli L (2017) Demand uncertainty in robust Home Care optimization. Omega 80:95–110. https://doi.org/10.1016/j.omega.2017.08.012

    Article  Google Scholar 

  5. Fathollahi-Fard AM, Hajiaghaei-Keshteli M, Tavakkoli-Moghaddam R (2018) A bi-objective green home health care routeing problem. J Clean Prod 200:423–443

    Article  Google Scholar 

  6. Liu R, Xie X, Augusto V, Rodriguez C (2013) Heuristic algorithms for a vehicle routing problem with simultaneous delivery and pickup and time windows in home health care. Eur J Oper Res 230(3):475–486

    Article  MathSciNet  MATH  Google Scholar 

  7. Liu R, Xie X, Garaix T (2014) Hybridization of tabu search with feasible and infeasible local searches for periodic home health care logistics. Omega 47:17–32

    Article  Google Scholar 

  8. Fikar C, Hirsch P (2015) A matheuristic for routing real-world home service transport systems facilitating walking. J Clean Prod 105:300–310

    Article  Google Scholar 

  9. Harris MD (2015) Handbook of home health care administration. Jones & Bartlett Publishers, Burlington

    Google Scholar 

  10. Braekers K, Hartl RF, Parragh SN, Tricoire F (2016) A bi-objective home care scheduling problem: analyzing the trade-off between costs and client inconvenience. Eur J Oper Res 248(2):428–443

    Article  MathSciNet  MATH  Google Scholar 

  11. Fathollahi-Fard AM, Hajiaghaei-Keshteli M, Tavakkoli-Moghaddam R (2018) A Lagrangian relaxation-based algorithm to solve a Home Health Care routing problem. Int J Eng Trans A Basics 31(10):1734–1740

    Google Scholar 

  12. Begur SV, Miller DM, Weaver JR (1997) An integrated spatial DSS for scheduling and routing home-health-care nurses. Interfaces 27(4):35–48

    Article  Google Scholar 

  13. Cheng E, Rich JL (1998) A home health care routing and scheduling problem. Houston, Texas

    Google Scholar 

  14. Bertels S, Fahle T (2006) A hybrid setup for a hybrid scenario: combining heuristics for the home health care problem. Comput Oper Res 33(10):2866–2890

    Article  MATH  Google Scholar 

  15. Eveborn P, Flisberg P, Rönnqvist M (2006) Laps Care—an operational system for staff planning of home care. Eur J Oper Res 171(3):962–976

    Article  MATH  Google Scholar 

  16. Akjiratikarl C, Yenradee P, Drake PR (2007) PSO-based algorithm for home care worker scheduling in the UK. Comput Ind Eng 53(4):559–583

    Article  Google Scholar 

  17. Trautsamwieser A, Gronalt M, Hirsch P (2011) Securing home health care in times of natural disasters. OR Spectrum 33(3):787–813

    Article  MathSciNet  MATH  Google Scholar 

  18. Eveborn P, Rönnqvist M, Einarsdóttir H, Eklund M, Lidén K, Almroth M (2009) Operations research improves quality and efficiency in home care. Interfaces 39(1):18–34

    Article  Google Scholar 

  19. Kergosien Y, Lenté C, Billaut JC (2009) Home health care problem: An extended multiple traveling salesman problem. In: Proceedings of the 4th multidisciplinary international scheduling conference: theory and applications (MISTA 2009), pp 85–92

  20. Rasmussen MS, Justesen T, Dohn A, Larsen J (2012) The home care crew scheduling problem: preference-based visit clustering and temporal dependencies. Eur J Oper Res 219(3):598–610

    Article  MATH  Google Scholar 

  21. Nickel S, Schröder M, Steeg J (2012) Mid-term and short-term planning support for home health care services. Eur J Oper Res 219(3):574–587

    Article  MATH  Google Scholar 

  22. Mankowska DS, Meisel F, Bierwirth C (2014) The home health care routeing and scheduling problem with interdependent services. Health Care Manag Sci 17(1):15–30

    Article  Google Scholar 

  23. Hiermann G, Prandtstetter M, Rendl A, Puchinger J, Raidl GR (2015) Metaheuristics for solving a multimodal home-healthcare scheduling problem. CEJOR 23(1):89–113

    Article  MathSciNet  MATH  Google Scholar 

  24. Wolpert DH, Macready WG (1997) No free lunch theorems for optimization. IEEE Trans Evol Comput 1(1):67–82

    Article  Google Scholar 

  25. Fathollahi Fard AM, Hajiaghaei-Keshteli M (2018) A bi-objective partial interdiction problem considering different defensive systems with capacity expansion of facilities under imminent attacks. Appl Soft Comput 68:343–359

    Article  Google Scholar 

  26. Hajiaghaei-Keshteli M, Fathollahi-Fard AM (2018) A set of effective heuristics and metaheuristics to solve the two-stage stochastic bi-level decision-making model for the distribution network problem. Comput Ind Eng 123:378–395

    Article  Google Scholar 

  27. Dukkanci O, Kara BY (2017) Routeing and scheduling decisions in the hierarchical hub location problem. Comput Oper Res 85:45–57

    Article  MathSciNet  MATH  Google Scholar 

  28. Mestria M (2018) New hybrid heuristic algorithm for the clustered traveling salesman problem. Comput Ind Eng 116:1–12

    Article  Google Scholar 

  29. Golshahi-Roudbaneh A, Hajiaghaei-Keshteli M, Paydar MM (2017) Developing a lower bound and strong heuristics for a truck scheduling problem in a cross-docking center. Knowl-Based Syst 129:17–38

    Article  Google Scholar 

  30. Astorino A, Gaudioso M, Miglionico G (2018) Lagrangian relaxation for the directional sensor coverage problem with continuous orientation. Omega 75:77–86

    Article  Google Scholar 

  31. Miller CE, Tucker AW, Zemlin RA (1960) Integer programming formulation of traveling salesman problems. J ACM 7:326–329

    Article  MathSciNet  MATH  Google Scholar 

  32. Frifita S, Masmoudi M, Euchi J (2017) General variable neighborhood search for home healthcare routeing and scheduling problem with time windows and synchronized visits. Electron Notes Discret Math 58:63–70

    Article  MATH  Google Scholar 

  33. Selvanambi R, Natarajan J, Karuppiah M, Islam SH, Hassan MM, Fortino G (2018) Lung cancer prediction using higher-order recurrent neural network based on glowworm swarm optimization. Neural Comput Appl 1–14

  34. Fathollahi-Fard AM, Hajiaghaei-Keshteli M, Mirjalili S (2018) Multi-objective stochastic closed-loop supply chain network design with social considerations. Appl Soft Comput 71:505–525

    Article  Google Scholar 

  35. Hajiaghaei-Keshteli M, Fathollahi Fard AM (2018) Sustainable closed-loop supply chain network design with discount supposition. Neural Comput Appl. https://doi.org/10.1007/s00521-018-3369-5

  36. Fathollahi-Fard AM, Hajiaghaei-Keshteli M, Mirjalili S (2018) “Hybrid optimizers to solve a tri-level programming model for a tire closed-loop supply chain network design problem. Appl Soft Comput 70:701–722

    Article  Google Scholar 

  37. Sahebjamnia N, Fathollahi-Fard AM, Hajiaghaei-Keshteli M (2018) Sustainable tire closed-loop supply chain network design: hybrid metaheuristic algorithms for large-scale networks. J Clean Prod 196:273–296

    Article  Google Scholar 

  38. Aliakbarian N, Dehghanian F, Salari M (2015) A bi-level programming model for protection of hierarchical facilities under imminent attacks. Comput Oper Res 64:210–224

    Article  MathSciNet  MATH  Google Scholar 

  39. Golmohamadi S, Tavakkoli-Moghaddam R, Hajiaghaei-Keshteli M (2017) Solving a fuzzy fixed charge solid transportation problem using batch transferring by new approaches in meta-heuristic. Electr Notes Discret Math 58:143–150

    Article  MathSciNet  MATH  Google Scholar 

  40. Sadeghi-Moghaddam S, Hajiaghaei-Keshteli M, Mahmoodjanloo M (2017) New approaches in metaheuristics to solve the fixed charge transportation problem in a fuzzy environment. Neural Comput Appl. https://doi.org/10.1007/s00521-017-3027-3

    Article  Google Scholar 

  41. Snyder LV, Daskin MS (2006) A random-key genetic algorithm for the generalized traveling salesman problem. Eur J Oper Res 174(1):38–53

    Article  MathSciNet  MATH  Google Scholar 

  42. Fathollahi-Fard AM, Hajiaghaei-Keshteli M, Tavakkoli-Moghaddam R (2018) The Social Engineering Optimizer (SEO). Eng Appl Artif Intell 72:267–293

    Article  Google Scholar 

  43. Fathollahi-Fard AM, Hajiaghaei-Keshteli M (2018) A stochastic multi-objective model for a closed-loop supply chain with environmental considerations. Appl Soft Comput 69:232–249

    Article  Google Scholar 

  44. Taguchi G (1986) Introduction to quality engineering: designing quality into products and processes

Download references

Funding

The authors of this research certify that they have no affiliation with or involvement in any organization or entity with financial interest (such as honoraria; educational grants; participation in speakers’ bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements) or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript.

Author information

Authors and Affiliations

  1. Department of Industrial Engineering and Management Systems, Amirkabir University of Technology, Tehran, Iran

    Amir Mohammad Fathollahi-Fard

  2. Department of Industrial Engineering, University of Science and Technology of Mazandaran, Behshahr, Iran

    Mostafa Hajiaghaei-Keshteli

  3. Institute for Integrated and Intelligent Systems, Griffith University, Nathan, QLD, 4111, Australia

    Seyedali Mirjalili

Authors
  1. Amir Mohammad Fathollahi-Fard
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mostafa Hajiaghaei-Keshteli
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Seyedali Mirjalili
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Amir Mohammad Fathollahi-Fard.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 1259 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fathollahi-Fard, A.M., Hajiaghaei-Keshteli, M. & Mirjalili, S. A set of efficient heuristics for a home healthcare problem. Neural Comput & Applic 32, 6185–6205 (2020). https://doi.org/10.1007/s00521-019-04126-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00521-019-04126-8

Keywords

Search

Navigation