Hybrid genetic algorithm to federal government capital budgetting

Volume: 2 Number: 1 March 1, 2017
  • D. Hakimi
  • D. O. Oyewola
  • K.r. Adeboye
  • R.o. Olayiwola
Communication in Mathematical Modeling and Applications Cover
Communication in Mathematical Modeling and Applications
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Hybrid genetic algorithm to federal government capital budgetting

Abstract

Multidimensional Knapsack problem is a NP-hard problem. The problem has been studied extensively in the literature. In this paper we provides a solution to a capital budgeting problem of Federal Government Budget in Nigeria using Hybrid Genetic Algorithms proposed by [32].We use also used the approach of [33] to model federal government budget by dividing the capital project into four groups which includes : The Economic sector (x1) , The Social Service sector (x2), The Environmental/Regional Development sector (x3), and The Administration sector (x4). Using MATLAB software for the analysis, it was observed that the optimal solution was optimal solution value is 277.64 billion naira. The result shows that the first and the second sector will be selected (x1, x2 = 1;x3, x4 = 0).

Keywords

Details

Primary Language

English

Subjects

-

Journal Section

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Authors

D. Hakimi This is me

D. O. Oyewola This is me

K.r. Adeboye This is me

R.o. Olayiwola This is me

Publication Date

March 1, 2017

Submission Date

March 1, 2017

Acceptance Date

-

Published in Issue

Year 2017 Volume: 2 Number: 1

IZ

https://izlik.org/JA32PS88GZ

Cite

RIS / Bibtex
APA
Hakimi, D., Oyewola, D. O., Adeboye, K., & Olayiwola, R. (2017). Hybrid genetic algorithm to federal government capital budgetting. Communication in Mathematical Modeling and Applications, 2(1), 16-22. https://izlik.org/JA32PS88GZ
AMA
1.Hakimi D, Oyewola DO, Adeboye K, Olayiwola R. Hybrid genetic algorithm to federal government capital budgetting. CMMA. 2017;2(1):16-22. https://izlik.org/JA32PS88GZ
Chicago
Hakimi, D., D. O. Oyewola, K.r. Adeboye, and R.o. Olayiwola. 2017. “Hybrid Genetic Algorithm to Federal Government Capital Budgetting”. Communication in Mathematical Modeling and Applications 2 (1): 16-22. https://izlik.org/JA32PS88GZ.
EndNote
Hakimi D, Oyewola DO, Adeboye K, Olayiwola R (March 1, 2017) Hybrid genetic algorithm to federal government capital budgetting. Communication in Mathematical Modeling and Applications 2 1 16–22.
IEEE
[1]D. Hakimi, D. O. Oyewola, K. Adeboye, and R. Olayiwola, “Hybrid genetic algorithm to federal government capital budgetting”, CMMA, vol. 2, no. 1, pp. 16–22, Mar. 2017, [Online]. Available: https://izlik.org/JA32PS88GZ
ISNAD
Hakimi, D. - Oyewola, D. O. - Adeboye, K.r. - Olayiwola, R.o. “Hybrid Genetic Algorithm to Federal Government Capital Budgetting”. Communication in Mathematical Modeling and Applications 2/1 (March 1, 2017): 16-22. https://izlik.org/JA32PS88GZ.
JAMA
1.Hakimi D, Oyewola DO, Adeboye K, Olayiwola R. Hybrid genetic algorithm to federal government capital budgetting. CMMA. 2017;2:16–22.
MLA
Hakimi, D., et al. “Hybrid Genetic Algorithm to Federal Government Capital Budgetting”. Communication in Mathematical Modeling and Applications, vol. 2, no. 1, Mar. 2017, pp. 16-22, https://izlik.org/JA32PS88GZ.
Vancouver
1.D. Hakimi, D. O. Oyewola, K.r. Adeboye, R.o. Olayiwola. Hybrid genetic algorithm to federal government capital budgetting. CMMA [Internet]. 2017 Mar. 1;2(1):16-22. Available from: https://izlik.org/JA32PS88GZ