Modified Goal Programming Model for Limited Available Budget Allocation for Equipment Procurement under Inflation Condition

Main Article Content

O. O. Ojo
P. K. Farayibi
B. O. Akinnuli


Equipment procurement budget is of a great challenge in manufacturing industries by reasons of its multi-objectives, insufficient funds, and inflation problems. Solutions were proffered to these problems by identifying the strategic decisions required in equipment procurement (machine, accessories, spare parts and miscellaneous costs). Procurement changes from year to year based on equipment industrial needs. Hence eleven (11) scenarios for procurement but this study focused on a scenario where all the decisions are needed for procurement. This problem is multi-objective decision problem where there is need for multi-objective decision tool for its solution, therefore a goal programming tool was adopted and improved by integrating inflation model into it to be able to solve inflation problems. International Brewery Ilesha, Nigeria was used as case study for the model’s application to evaluate its performance. The strategic decisions deviated above or positively by 0.4604, 4.1311 and 2.3760 for machines, spare-parts and miscellaneous costs respectively while accessories cost was not deviated. Therefore, the procurement cost for Machines, Accessories, Spare-parts and Miscellaneous costs would be (N 166,015,000; $ 461,152.77), (N 127,968,000; $ 355,466.67), (N 548,075,000; $ 1,522,430.56), (N 271,091,500; $ 753,031.94). US Dollar exchange rate was at N 360 to a Dollar as at the time of this research. This multi-criteria decision tool will find its application useful in small, medium and large scale industries that equipment procurement budget affects their production.v

Goal programming, available budget, equipment procurement, strategic decisions, inflation, multi-criteria model.

Article Details

How to Cite
Ojo, O. O., Farayibi, P. K., & Akinnuli, B. O. (2020). Modified Goal Programming Model for Limited Available Budget Allocation for Equipment Procurement under Inflation Condition. Advances in Research, 21(4), 25-35.
Original Research Article


Colapinto C, Jayaraman R, Marsiglio S. Multi-criteria decision analysis with goal programming in engineering, management and social sciences: A state-of-the art review. Annals of Operations Research. 2015;251(1-2):7–40.
DOI: 10.1007/s10479-015-1829-1

Akinnuli BO, Ojo OO, Balogun VA. Model developed for competing accessories, spare parts and miscellaneous costs for limited available budget under machine Availability. British journal of applied science and technology. 2016;16(3):1-8.
[Article No: BJAST.23025]
DOI: 10.9734/BJAST/2016/23025
[ISSN: 2231-0843]
[NLM ID: 101664541]

Adamu J, Bawuro MB. Inflation and economic growth nexus in Nigeria. International Journal of Innovative Research and Creative Technology. 2016; 2(3).
[ISSN: 2454-5988]

Jagdeep K, Pradeep T. Multi Objective optimization model using preemptive goal programming for software component selection. I. J. Information Technology and Computer Science. 2015;9:31-37
DOI: 10.5815/ijitcs.2015.09.05

Colapinto C, Jayaraman R, Marsiglio S. Multi-criteria decision analysis with goal programming inengineering, management and social sciences: a state-of-the art review. Annals of Operations Research. 2017;251(1-2):7-40.

Kliestik T, Misankova M, Bartosova. Application of multi criteria goal programming approach for management of the company. Applied Mathematical Sciences. 2015;9(0115):5715–5727.

Shikha T, Arun K. Comparison between goal programming and other linear programming methods. International Journal for Research in Applied Science & Engineering Technology (IJRASET); 2018.
[ISSN: 2321-9653]

Rama S, Srividya S, Deepa B. A linear programming approach for optimal scheduling of workers in a transport corporation. International Journal of Engineering Trends and Technology (IJETT). 2017;45(10):482-48.

Yahia-Berrouiguet A, Tissourassi K. Application of goal programming model for allocating time and cost in project management: A case study from the company of constructionseror. yugoslav Journal of Operations Research. 2015;25 (2):283-289
DOI: 10.2298/YJOR131010010Y10

Wong TE, Srikrishnan V, Hadka D, Keller K. A multi-objective decision-making approach to the journal submission problem. PLoSONE. 2017;12(6): e0178874.

Eichfelder G, Krüger C, Schöbel A. Decision uncertainty inmultiobjective optimization. JGlob Optim. 2017;69(2): 485–510.

Oyebode OJ. Budget and Budgetary Control: A pragmatic approach to the Nigerian infrastructure dilemma. World Journal of Research and Review (WJRR). Budget and Budgetary Control: A Pragmatic Approach to the Nigerian Infrastructure Dilemma. 2018;7(3):1-8.
[ISSN: 2455–3956]
[Accessed Mar 15 2020]

Wonder A, Frank OD, Wang S. Budgeting and its effect on the financial performance of listed manufacturing firms: Evidence from manufacturing firms listed on Ghana stock exchange. Research Journal of Finance and Accounting. 2018;9(8).
[ISSN: 2222-1697] (Paper)
[ISSN: 2222-2847] (Online)

Tatiana MK, Oleg AK, Alla GG, Veronica VN, Denis EG. The Budgeting mechanism in development companies. International Journal of Environmental & Science Education. 2016;11(15):7726- 7744.

Derfuss K. Reconsidering the participative budgeting-performance relation: A meta-analysis regarding the impact of level of analysis, sample selection, measurement, and industry influences. The British Accounting Review. 2016;48(1):17- 37.

Ojo OO, Akinnuli BO, Farayibi PK. Data mining and statistical analysis for available budget allocation pre-procurement of manufacturing equipment. Journal of Engineering Research and Reports. 2019; 5(3):1-13.

Joseph O, John A. Monetary policy and inflation targeting in Nigeria. International Journal of Economics and Financial Management. 2017;2(3).
[ISSN: 2545-5966]