Research Article
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Year 2019, Volume: 3 Issue: 2, 283 - 289, 31.12.2019

Abstract

References

  • Alanne, K., Selection of renovation actions using multi-criteria "knapsack" model, Automation in Construction, 13 (3), 377-391, (2004).
  • Bakirli, B., Gencer, C., Aydoğan, E., A combined approach for fuzzy multi-objective multiple knapsack problems for defence project selection, Journal of the Operational Research Society, 65(7), 1001–1016, (2014).
  • Bas E., A capital budgeting problem for preventing workplace mobbing by using analytic hierarchy process and fuzzy 0-1 bidimensional knapsack model, Expert Systems with Applications, 38(10), 12415-12422, (2011).
  • Chang P.T., Lee J.H., A fuzzy DEA and knapsack formulation integrated model for project selection, Computers and Operations Research, 39 (1), 112-125, (2012).
  • Dağdeviren, M., Yavuz, S., Kılınç, N., Weapon Selection Using the AHP and TOPSIS Methods Under Fuzzy Environment, Expert Systems with Applications, 36 (4), 8143–8151, (2009).
  • de Souza, J.S., Neto, J.K., Filomena, T.P., Anzanello, M., A Non-Traditional Capital Investment Criteria-Based Method To Optimize A Portfolio Of Investments, International Journal of Industrial Engineering: Theory, Applications and Practice, 19(4), 193-203, (2012).
  • Husbands, R., Ahmed, Q., Wang, J., Transmit antenna selection for massive MIMO: A knapsack problem formulation, 2017 IEEE International Conference on Communications (ICC), Paris, 1-6, (2017).
  • Ic, Y.T., Özel, M., Kara I., An Integrated Fuzzy TOPSIS-Knapsack Problem Model for Order Selection in a Bakery, Arabian Journal of Science and Engineering, 47, 5321-5337, (2017).
  • Klamler C., Pferschy U., Ruzika S., Committee Selection with a Weight Constraint Based on Lexicographic Rankings of Individuals, In: Rossi F., Tsoukias A. (eds) Algorithmic Decision Theory, ADT 2009, Lecture Notes in Computer Science, 5783, Springer, Berlin, Heidelberg (2009).
  • Lorie, J.H., Savage, L.J., Three Problems in Rationing Capital, The Journal of Business, 28, 229-239, (1955).
  • Marinoni, O., Higgins, A., Hajkowicz, S., A multi criteria knapsack solution to optimise natural resource management project selection, Lecture Notes in Economics and Mathematical Systems, 634, 47-55, (2010).
  • Markhvida, M., Baker, J. W., Unification of seismic performance estimation and real estate investment analysis to model post-earthquake building repair decisions, Earthquake Spectra, 34(4), 1787-1808, (2018).
  • Mulvey, J. M., Vladimirou, H., Stochastic Network Optimization Models for Investment Planning, Annals of Operations Research, 20, 187-217, (1989)
  • O’Leary D.E., Financial planning with 0–1 knapsack problems part 1: Domination results. Advances in Mathematical Programming and Financial Planning, 4(1), 139–150, (1995).
  • Rouyendegh B. D., Erkan, T. E., Selection the best supplier using AHP method, African Journal of Business Management, 6(4), 1454–1462, (2012).
  • Saaty, T. L., The analytic hierarchy process, McGraw-Hill, New York, (1980).
  • Yavuz, S., Captain, T. A., Making project selection decisions: a multi-period capital budgeting problem. International Journal of Industrial Engineering, 9(3), 301-310, (2002).

AHP – Binary Linear Programming Approach for Multiple Criteria Real Estate Investment Planning

Year 2019, Volume: 3 Issue: 2, 283 - 289, 31.12.2019

Abstract

Capital allocation on real estate investments must be made after
careful consideration. An investor can obtain a great amount of revenue with a
good investment, however, an investment can result by waste of capital, which
is spent on an unprofitable asset. There are different aspects of investments related
to economic, legal, location and physical factors, which should be taken into
account in assessment of possible investment options. In this study, real
estate investment planning problem is considered as a multi-objective knapsack
problem. An integrated AHP – Binary Linear Programming model is proposed to
determine the best investment plan considering different criteria
simultaneously. Within the proposed model, multi-criteria evaluation of
investment alternatives is done by using Analytical Hierarchy Process and
obtained criteria weights values are written as the objective function
coefficient in the knapsack model. A real estate investment planning
application, which contains 10 alternatives in Ankara, is presented to test the
applicability of the proposed decision model. Obtained results are compared
with the results obtained by only considering financial aspects of investment. 

References

  • Alanne, K., Selection of renovation actions using multi-criteria "knapsack" model, Automation in Construction, 13 (3), 377-391, (2004).
  • Bakirli, B., Gencer, C., Aydoğan, E., A combined approach for fuzzy multi-objective multiple knapsack problems for defence project selection, Journal of the Operational Research Society, 65(7), 1001–1016, (2014).
  • Bas E., A capital budgeting problem for preventing workplace mobbing by using analytic hierarchy process and fuzzy 0-1 bidimensional knapsack model, Expert Systems with Applications, 38(10), 12415-12422, (2011).
  • Chang P.T., Lee J.H., A fuzzy DEA and knapsack formulation integrated model for project selection, Computers and Operations Research, 39 (1), 112-125, (2012).
  • Dağdeviren, M., Yavuz, S., Kılınç, N., Weapon Selection Using the AHP and TOPSIS Methods Under Fuzzy Environment, Expert Systems with Applications, 36 (4), 8143–8151, (2009).
  • de Souza, J.S., Neto, J.K., Filomena, T.P., Anzanello, M., A Non-Traditional Capital Investment Criteria-Based Method To Optimize A Portfolio Of Investments, International Journal of Industrial Engineering: Theory, Applications and Practice, 19(4), 193-203, (2012).
  • Husbands, R., Ahmed, Q., Wang, J., Transmit antenna selection for massive MIMO: A knapsack problem formulation, 2017 IEEE International Conference on Communications (ICC), Paris, 1-6, (2017).
  • Ic, Y.T., Özel, M., Kara I., An Integrated Fuzzy TOPSIS-Knapsack Problem Model for Order Selection in a Bakery, Arabian Journal of Science and Engineering, 47, 5321-5337, (2017).
  • Klamler C., Pferschy U., Ruzika S., Committee Selection with a Weight Constraint Based on Lexicographic Rankings of Individuals, In: Rossi F., Tsoukias A. (eds) Algorithmic Decision Theory, ADT 2009, Lecture Notes in Computer Science, 5783, Springer, Berlin, Heidelberg (2009).
  • Lorie, J.H., Savage, L.J., Three Problems in Rationing Capital, The Journal of Business, 28, 229-239, (1955).
  • Marinoni, O., Higgins, A., Hajkowicz, S., A multi criteria knapsack solution to optimise natural resource management project selection, Lecture Notes in Economics and Mathematical Systems, 634, 47-55, (2010).
  • Markhvida, M., Baker, J. W., Unification of seismic performance estimation and real estate investment analysis to model post-earthquake building repair decisions, Earthquake Spectra, 34(4), 1787-1808, (2018).
  • Mulvey, J. M., Vladimirou, H., Stochastic Network Optimization Models for Investment Planning, Annals of Operations Research, 20, 187-217, (1989)
  • O’Leary D.E., Financial planning with 0–1 knapsack problems part 1: Domination results. Advances in Mathematical Programming and Financial Planning, 4(1), 139–150, (1995).
  • Rouyendegh B. D., Erkan, T. E., Selection the best supplier using AHP method, African Journal of Business Management, 6(4), 1454–1462, (2012).
  • Saaty, T. L., The analytic hierarchy process, McGraw-Hill, New York, (1980).
  • Yavuz, S., Captain, T. A., Making project selection decisions: a multi-period capital budgeting problem. International Journal of Industrial Engineering, 9(3), 301-310, (2002).
There are 17 citations in total.

Details

Primary Language English
Subjects Industrial Engineering
Journal Section Research Article
Authors

Billur Ecer 0000-0001-9692-1450

Ahmet Aktas 0000-0002-4394-121X

Mehmet Kabak 0000-0002-8576-5349

Publication Date December 31, 2019
Submission Date November 15, 2019
Acceptance Date January 6, 2020
Published in Issue Year 2019 Volume: 3 Issue: 2

Cite

APA Ecer, B., Aktas, A., & Kabak, M. (2019). AHP – Binary Linear Programming Approach for Multiple Criteria Real Estate Investment Planning. Journal of Turkish Operations Management, 3(2), 283-289.
AMA Ecer B, Aktas A, Kabak M. AHP – Binary Linear Programming Approach for Multiple Criteria Real Estate Investment Planning. JTOM. December 2019;3(2):283-289.
Chicago Ecer, Billur, Ahmet Aktas, and Mehmet Kabak. “AHP – Binary Linear Programming Approach for Multiple Criteria Real Estate Investment Planning”. Journal of Turkish Operations Management 3, no. 2 (December 2019): 283-89.
EndNote Ecer B, Aktas A, Kabak M (December 1, 2019) AHP – Binary Linear Programming Approach for Multiple Criteria Real Estate Investment Planning. Journal of Turkish Operations Management 3 2 283–289.
IEEE B. Ecer, A. Aktas, and M. Kabak, “AHP – Binary Linear Programming Approach for Multiple Criteria Real Estate Investment Planning”, JTOM, vol. 3, no. 2, pp. 283–289, 2019.
ISNAD Ecer, Billur et al. “AHP – Binary Linear Programming Approach for Multiple Criteria Real Estate Investment Planning”. Journal of Turkish Operations Management 3/2 (December 2019), 283-289.
JAMA Ecer B, Aktas A, Kabak M. AHP – Binary Linear Programming Approach for Multiple Criteria Real Estate Investment Planning. JTOM. 2019;3:283–289.
MLA Ecer, Billur et al. “AHP – Binary Linear Programming Approach for Multiple Criteria Real Estate Investment Planning”. Journal of Turkish Operations Management, vol. 3, no. 2, 2019, pp. 283-9.
Vancouver Ecer B, Aktas A, Kabak M. AHP – Binary Linear Programming Approach for Multiple Criteria Real Estate Investment Planning. JTOM. 2019;3(2):283-9.

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