Acta Mechanica Slovaca 2019, 23(2):20-24 | DOI: 10.21496/ams.2019.002
Analysis of Mathematical Programming Applications in Supply Chain Management of Manufacturing Enterprises
- 1 Faculty of Economics, Institute of Managerial Systems, Matej Bel University, 910/8 Francisciho, Poprad 05801, Slovak republic
This paper focuses on a current topic of supply chain management and operations research which serves as a tool manufacturing enterprises to cope with pressure put on them by continuously changing market conditions and global economy itself. Paper presents results of research conducted on sample file of Slovak manufacturing enterprises. The main aim of this paper is to explore the extent of utilization of mathematical programming as optimization methods in production practice in Slovakia to analyse possible relationship between enterprise's size and used optimizing method. Representativeness of the sample file was confirmed by application of Pearson´s chi-squared test (χ2 - test) due to criterion of enterprise's size. The results of this research have an implication for business practice and may serve managers in their decision-making process. In managerial practice enterprises have to deal with many different problems concerning their supply chains. The majority of them can be resolved using mathematical programming.
Keywords: mathematical programming; supply chain management; manufacturing enterprises
Published: June 28, 2019 Show citation
References
- AL-YAKOOB, S.M. a SHERALI, H. 2007. Mixed-integer programming models for an employee scheduling problem with multiple shifts and work locations. Annals of Operations Research, 155(1): 119-142.
Go to original source...
- ARMUTLU, P. et al. 2008. Classification of drug molecules considering their IC50 values using mixed-integer linear programming based hyper-boxes method. BMC Bioinformatics, 9(1): 411-425.
Go to original source...
- AVIS, D. a UMEMOTO, J. 2003. Stronger linear programming relaxations of max-cut. Mathematical Programming, 97(3): 451-469.
Go to original source...
- BEN-TAL, A. a NEMIROVSKI, A. 2000. Robust solutions of Linear Programming problems contaminated with uncertain data. Mathematical Programming, 88(3): 411-424.
Go to original source...
- BRUGLIERI, M. et al. 2016. A new Mathematical Programming Model for the Green Vehicle Routing Problem. Electronic Notes in Discrete Mathematics, 55: 89-92.
Go to original source...
- CHADHA, S.S. a CHADHA, V. 2007. Linear fractional programming and duality. Central European Journal of Operations Research, 15(2): 119-125.
Go to original source...
- DAS, K. 2011. Integrating effective flexibility measures into a strategic supply chain planning model. European Journal of Operational Research, 211(1): 170-183.
Go to original source...
- FLOUDAS, C.A. a LIN, X. 2005. Mixed Integer Linear Programming in Process Scheduling: Modeling, Algorithms, and Applications. Annals of Operations Research, 139(1): 131-162.
Go to original source...
- GONG, Z. 2008. An economic evaluation model of supply chain flexibility. European Journal of Operational Research. 184(1): 745-758.
Go to original source...
- GROVER, V. a MALHOTRA, M.K. 2003. Transaction cost framework in operations and supply chain management research: theory and measurement. Journal of Operations Management. 21(4): 457-473.
Go to original source...
- LIAO, H. et al. 2016. Measuring energy economic efficiency:A mathematical programming approach. Applied Energy, 179: 479-487.
Go to original source...
- MALHOTRA, M.K, SINGHAL, C., SHANG, G. a PLOYHART, R.E. 2014. A critical evaluation of alternative methods and paradigms for conducting mediation analysis in operations management research. Journal of Operations Management. 32(4): 127-137.
Go to original source...
- Maloney, T. A Byard, K. (2013). Quantitative Methods for Business. Pearson New Zealand Publishing, Auckland.
- SODHI, M.S. a TANG, C.S. 2012. Strategic approaches for mitigating supply chain risks. International Series in Operations Research & Management Science, 172(1): 95-108.
Go to original source...
- THOAI, N.V. 2010. Reverse Convex Programming Approach in the Space of Extreme Criteria for Optimization over Efficient Sets. Journal of Optimization Theory and Applications, 147(2): 263-277.
Go to original source...
- THUAN, L.V. a LUC, D.T. 2000. On Sensitivity in Linear Multiobjective Programming. Journal of Optimization Theory and Applications, 107(3): 615-626.
Go to original source...
- TIBI, N.A. a ARMAN, H. 2007. A linear programming model to optimize the decision-making to managing cogeneration system. Clean Technologies and Environmental Policy, 9(3): 235-240.
Go to original source...
- Veselovská, L. (2015). Analysis of various measures to increase flexibility in supply chains of Slovak enterprises. In Ekonomika a spoločnosť - Journal of Economics and Social Research, Vol. 16, No. 2, pp. 155-162.
- VLACHOS, A.G., DOURBOIS, G.A. a BISKAS, P.N. 2016. Comparison of two mathematical programming models for the solution of a convex portfolio-based European day-ahead electricity market. Electric Power Systems Research, 141: 313-324.
Go to original source...
- WEBER, G. W. 2009. Continuous Optimization in Finance. Optimization: A journal of Mathematical Programming and Operations Research, 58(3): 263-265.
Go to original source...
- XU, G. et al. 2016. Mathematical programming methods for consistency and consensus in group decision making with intuitionistic fuzzy preference relations. Knowledge-Based Systems, 98: 30-43.
Go to original source...
- ZÁVADSKÝ, J. a ZÁVADSKÁ, Z. 2014. Utilisation of business process models in managerial practice: An empirical study in Slovak enterprises certified to the ISO 9001 standard. Total Quality Management & Business Excellence. 24(3-4): 319-337.
Go to original source...
- ZÁVADSKÝ, J. a HIADLOVSKÝ, V. 2014. The consistency of performance management system based on attributes of the performance indicator: An empirical study. Quality Innovation Prosperity. 18(1): 93-106.
Go to original source...
This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.