ERP Selection Using Fuzzy-MOGA Approach: A Food Enterprise Case Study

Joko Ratono, Kudang Boro Seminar, Yandra Arkeman, Arif Imam Suroso


Selection of Enterprise Resource Planning (ERP) system is a complex decision-making process and one of the critical success factors (CSFs) in ERP adoption life cycle. Many ERP implementation failures are caused by improper package selection. Various approaches have been used, but not using optimization techniques. This study developed a Fuzzy-Multiobjective Genetic Algorithm (Fuzzy-MOGA) approach to optimize the quality of ERP selection criteria that complies with ISO25010 quality standard and cost. A case study was conducted on an agro-industrial company. The result shows the approach of Fuzzy-MOGA with NSGA-II method facilitate a complex decision-making for ERP selection optimally.


ERP Selection; Fuzzy-MOGA; NSGA-II; ISO25010; Agro-Industry

Full Text:



Rayner N, Woods J. ERP Strategy: Why Do You Need One and Key Considerations for Defining One. Gartner RAS Core Research. 2011; 2(4):1-9.

Ghosh R. A Comprehensive Study on ERP Failures Stressing on Reluctance to Change as a Cause of Failure. Journal of Marketing and Management. 2012; 3(1): 123-134.

Panorama CG. 2013 ERP Report. A Panorama Consulting Solutions Research Report. 2013.

Gupta PC, Kumar A. Evaluation of ERP Life Cycle on the Scale of ERP Implementation Failure. International Journal of Research in IT, Management and Engineering. 2012; 2(8):61-68.

Munkelt T, Volker S. ERP systems: aspects of selection, implementation and sustainable operations. International Journal of Information Systems and Project Management. 2013; 1(2): 25-39.

Dezdar S, Ainin S. Critical Success Factors for Erp Implementation: Insights from a Middle-Eastern Country. Middle-East Journal of Scientific Research. 2011; 10(6): 798-808.

Sanchez NG, Bernal LEP. Determination of Critical Success Factors in Implementing an ERP System: A Field Study in Mexican Enterprises. Information Technology for Development. 2013; 13(3): 293–309.

Uta A, Intorsureanu I, Mihalca R. Criteria for The Selection of ERP software. Informatica Economica. 2007; 2(42): 63-66.

Ratono J, Seminar KB, Arkeman Y, Suroso AI. The Development of Enterprise Resource Planning (ERP) Selection Methodology Using Delta Model. International Journal of Information Technology and Business Management. 2014; 31(1): 1-12.

Fisher DM, Fisher SA, Kiang MY. Evaluating mid-level ERP software. Journal of Computer Information Systems. 2004; 45(1):38-46.

Wei CC, Chien CF, Wang MJJ. An AHP-based approach to ERP system selection. International Journal of Production Economics. 2005; 96(1): 47-62.

Liao XW, Li Y, Lu B. A model for selecting an ERP system based on linguistic information processing. Information Systems. 2007; 32(7): 1005-1017.

Shyur HJ. A Semi-Structured Process for ERP Systems Evaluation: Applying Analytic Network Process. Journal of e-Business. 2003; 5(1): 105-122.

Ayag Z. Evaluating simulation software alternatives through ANP. Proceedings of the 2011 International Conference on Industrial Engineering and Operations Management. Kuala Lumpur. 2011;

Wei CC, Wang MJJ. A comprehensive framework for selecting an ERP system. International Journal of Project Management. 2004; 22(2): 161-169.

Asgari M, Allahverdiloo M, Samkhani S. A Comprehensive Framework for Selecting the ERP System in Iran Khodro Company. European Journal of Economics, Finance and Administrative Sciences. 2011; 38(2011): 7-19.

Lien CT, Chan HS. A Selection Model for ERP System by Applying Fuzzy AHP Approach. International Journal of The Computer, the Internet and Managemen. 2007; 15(3): 58-72.

Onut S, Efendigil T. A theorical model design for ERP software selection process under the constraints of cost and quality: A fuzzy approach. Journal of Intelligent & Fuzzy Systems. 2010; 21(6): 365-378.

Ayağ Z, Özdemir RG. An intelligent approach to ERP software selection through fuzzy ANP. International Journal of Production Research. 2007; 45(10): 2169-2194.

Cebeci U. Fuzzy AHP-based decision support system for selecting ERP systems in textile industry by using balanced scorecard. Journal Expert System Applications. 2009; 36(5):8900-8909.

Karsak EE, Özogul CO. An integrated decision making approach for ERP system selection. Journal Expert System Applications. 2009; 36(1): 660-667.

Yazgan HR, Boran S, Goztepe K. An ERP software selection process with using artificial neural network based on analytic network process approach. Journal Expert System Applications. 2009; 36(5): 9214-9222.

Ozalp V, Yigit O, Maria MC. ERP consultant selection problem using AHP, fuzzy AHP and ANP: A case study in Turkey. E3 Journal of Business Management and Economics. 2012; 3(3): 106-117.

Erol I, Barut M. Developing knowledge based decision support tool for enterprise resources planning (ERP) software selection. Ankara Üniversitesi Siyasal Bilgiler Fakültesi Dergisi. 2003; 58(1):72-96.

Olson DL, Wu DD. Multiple Criteria Analysis for Evaluation of Information System Risk. Asia-Pacific Journal of Operational Research. 2011; 28(1): 1-25.

Jahanshahi H, Farhadzareh B, Fotuhi H, Golpour A, Mokhtari MB. A New Algorithm for ERP System Selection Based on Fuzzy DEMATEL Approach. Advances in Environmental Biology. 2013; 7(9): 2509-2521.

ISO/IEC 25010. Systems and software engineering - Systems and software Quality Requirements and Evaluation (SQuaRE) - Quality model. 2011.

Vorst CV. Approach for Selecting ERP Software at Mid-sized Companies Reflecting Critical Success Factors. Journal of US-China Public Administration. 2012; 9(9): 1057-1068.

Chu TC, Lin RH. Evaluating Suppliers via a Total Integral Value based Fuzzy MCDM Approach. Asia Pacific Management Review. 2011; 16(4): 521-534.

Deb K, Agrawal S, Pratap A, Meyarivan T. A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II. In: proceedings of the parallel problem solving from nature VI (PPSN-VI) conference. 2002.

Rezaei J, Davoodi M. Multi-objective models for lot-sizing with supplier selection. International Journal Production Economics. 2011; 130(2011): 77-86.

Luo YL, Liu M, Hao Z, Liu D. An improved NSGA-II algorithm for multi-objective travelling salesman problem. Telkomnika. 2014; 12(6): 4413-4418

Qizuang, Yang G, Tang R, Xiang G. Multi-objective optimization algorithms design based on support vector regression metamodelling. Telkomnika. 2013; 11(11): 6406-6412.

Ponsich A, Azzaro-Pantel C, Domenech S, Pibouleau L. Constraint handling strategies in genetic algorithms application to optimal batch plant design. Chemical Engineering and Processing: Process Intensification. 2008; 47(3): 265-514.

Venter G. Review of Optimization Techniques. Encyclopedia of Aerospace Engineering. South Africa. 2010.

Arkeman Y, Seminar, KB, Gunawan H. Algoritma Genetika: Teori dan Aplikasinya untuk Bisnis dan Industri. Bogor (ID): IPB Press. 2012.

Haines AL, Mills KL, Filliben JJ. Determining relative importance and best settings for genetic algorithm control parameters. Evolutionary Computation. 2010; 2010(1): 1-22.

Rexhepi A, Maxhuni A, Dika A. Analysis of the impact of parameters values on the Genetic Algorithm for TSP. International Journal of Computer Science Issues. 2013;10(1): 158-164.

Reed P, Minsher B, Goldberg DE. Designing a competent simple genetic algorithm for search and optimization. Water Resources Research. 2000; 36(12): 3757-3761.

Deviredd V, Reed P. An Efficient Design Methodology for the Nondominated Sorted Genetic Algorithm-II. Genetic and Evolutionary Computation Conference (GECCO 03). Chicago. 2003.


Article Metrics

Abstract view : 304 times
PDF - 217 times


  • There are currently no refbacks.

Copyright (c) 2015 Universitas Ahmad Dahlan

TELKOMNIKA Telecommunication, Computing, Electronics and Control
ISSN: 1693-6930, e-ISSN: 2302-9293
Universitas Ahmad Dahlan, 4th Campus, 9th Floor, LPPI Room
Jl. Ringroad Selatan, Kragilan, Tamanan, Banguntapan, Bantul, Yogyakarta, Indonesia 55191
Phone: +62 (274) 563515, 511830, 379418, 371120 ext. 4902, Fax: +62 274 564604

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.