DESIGNING AN OUTPATIENT-APPOINTMENT
SCHEDULING USING AHP AND SIMULATED ANNEALING
Yousef Khawaled1, Mahmoud Alrefaei1,
Mahmoud Smadi1, Ameen Alawneh2
1Jordan University of Science and Technology
Irbid, 22110, JORDAN
2 Jadara University, Irbid, 22110, JORDAN

Abstract

In this paper, we consider the problem of designing an efficient appointment system of an outpatient department of a healthcare system in order to optimize the performance of the clinic. This problem includes optimizing three objectives, therefore it is considered as a multi-objective optimization problem (MOOP). One way for solving the MOOP is to use the weighted sum method at which all objectives are aggregated into a single objective using relative weights for each objective based on their importance, then one can use any optimization method to solve the aggregated problem. The analytic hierarchy process (AHP) is used to select these relative weights, then the simulated annealing (SA) method is implemented to solve the aggregated optimization problem. The proposed AHP-SA algorithm is used to solve a real case appointment system. The obtained numerical results indicate that the proposed method indeed gives relatively good solutions based on the importance level of each objective.

Citation details of the article



Journal: International Journal of Applied Mathematics
Journal ISSN (Print): ISSN 1311-1728
Journal ISSN (Electronic): ISSN 1314-8060
Volume: 35
Issue: 2
Year: 2022

DOI: 10.12732/ijam.v35i2.6

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References

  1. [1] P. JM Laarhoven, E. HL Aarts, Simulated Annealing: Theory and Applications, Kluwer Academic Publishers, Dordrecht, The Netherlands (1987).
  2. [2] M.H. Alrefaei, A. Nahiah, A. Abu-Lebda, D. Khayal, Simulating and optimizing scheduling system of outpatient department, In: Proc. International Conference on Operational Research and Statistics (ORS 2011) April (2011), 7–8.
  3. [3] M.H. Alrefaei, S. Andradóttir, A simulated annealing algorithm with constant temperature for discrete stochastic optimization, Manag. Sci., 45, No 5 (1999), 748–764.
  4. [4] M.H. Alrefaei, A. Diabat, Modelling and optimization of outpatientappointment scheduling, RAIRO-Oper. Res., 49, No 3 (2015), 435–450.
  5. [5] M.H. Alrefaei, A. Diabat, A simulated annealing technique for multiobjective simulation optimization, App. Math. Comp., 215, No 8 (2009), 3029–3035.
  6. [6] G. Crawford, C. Williams, A note on the analysis of subjective judgment matrices, J. Math. Psy., 29, No 4 (1985), 387–405.
  7. [7] R.E. Jensen, An alternative scaling method for priorities in hierarchical structures. J. Math. Psy., 28, No 3 (1984), 317–332.
  8. [8] S-H. Kim, W. Whitt, W.C. Cha, A data-driven model of an appointmentgenerated arrival process at an outpatient clinic, INFORMS J. Comp., 30, No 1 (2018), 181–199.
  9. [9] S. Kirkpatrick, C.D. Gelatt, M.P. Vecchi, Optimization by simulated annealing, Science, 220, No 4598 (1983), 671–680.
  10. [10] N. Metropolis, A.W. Rosenbluth, M.N. Rosenbluth, A.H. Teller, E. Teller, Equation of state calculations by fast computing machines. J. Chem. Phys., 21, No 6 (1953), 1087-–1092.
  11. [11] I. Palcic, Analytical hierarchy process as a tool for selecting and evaluating projects, Int. J. Sim. Mod., 8, No 3 (2009), 16–26.
  12. [12] T.L. Saaty, A scaling method for priorities in hierarchical structures, J. Math. Psy., 15, No 3 (1977), 234–281.
  13. [13] T.L. Saaty, G. Hu, Ranking by eigenvector versus other methods in the analytic hierarchy process, App. Math. Lett., 11, No 4 (1998), 121–125.
  14. [14] T.L. Saaty, The Analytic Hierarchy Process, Mc-Graw Hill, New York (1980).
  15. [15] J. Koski, R. Silvennoinen, Norm methods and partial weighting in multicriterion optimization of structures, Int. J. Num. Meth. Eng., 24, No 6 (1987), 1101–1121.
  16. [16] P.H. Santos, S.M. Neves, D.O. Sant’Anna, C.H. De Oliveira, H.D. Carvalho, The analytic Hierarchy Process Supporting Decision Making for Sustainable Development: An overview of applications, J. Clean. Prod., 212 (2019), 119–138.
  17. [17] P. Serafini, Multiple criteria decision making, In: Simulated Annealing for Multi Objective Optimization Problems, Springer (1994), 283–292.
  18. [18] N. Subramanian, R. Ramanathan, A review of applications of analytic hierarchy process in operations management, Int. J. Prod. Eco., 138, No 2 (2012), 215–241.