A Fuzzy Logic Algorithm for Optimizing the Investment Decisions within Companies

As companies operate in a competitive environment, where the struggle for survival on the market is rather tough, the top management face new challenges to identify methods, and even techniques, which allows it to select from the market those assets that provide an optimal ratio between the acquisition cost and the economic performance. In this context, a fuzzy logic managerial decision tool for the assets acquisition is proposed with the paper. The algorithm has three main components: the matrix of the membership degree of the existing bids to asset selection criteria, using fuzzy triangular numbers; the vector of the global membership degree of the bids to the selection criteria and the maximum of the global membership degree as an inference operator for establishing the validated bids by the algorithm. Two scenarios of asset acquisition were tested. After simulations, it was determined that the proposed fuzzy logic managerial decision tool combines, with very good results, the acquisition cost of the assets with their economic performance.

[1]  Gwo-Hshiung Tzeng,et al.  Fuzzy Inference-Enhanced VC-DRSA Model for Technical Analysis: Investment Decision Aid , 2015, International Journal of Fuzzy Systems.

[2]  Andreas Schilling,et al.  A framework for secure IT operations in an uncertain and changing environment , 2017, Comput. Oper. Res..

[3]  Minxia Luo,et al.  A Novel Similarity Measure for Interval-Valued Intuitionistic Fuzzy Sets and Its Applications , 2018, Symmetry.

[4]  Kuang Yu Huang,et al.  A hybrid model for stock market forecasting and portfolio selection based on ARX, grey system and RS theories , 2009, Expert Syst. Appl..

[5]  Xiaohong Zhang,et al.  New Similarity Measures of Single-Valued Neutrosophic Multisets Based on the Decomposition Theorem and Its Application in Medical Diagnosis , 2018, Symmetry.

[6]  E. Ertugrul Karsak,et al.  An integrated decision making approach for ERP system selection , 2009, Expert Syst. Appl..

[7]  Jun Wu,et al.  Selection of optimum maintenance strategies based on a fuzzy analytic hierarchy process , 2007 .

[8]  Mikael Collan,et al.  Possibilistic risk aversion in group decisions: theory with application in the insurance of giga-investments valued through the fuzzy pay-off method , 2017, Soft Comput..

[9]  Jie He,et al.  A Forecasting Model Based on Multi-Valued Neutrosophic Sets and Two-Factor, Third-Order Fuzzy Fluctuation Logical Relationships , 2018, Symmetry.

[10]  Florentin Smarandache,et al.  Triangular Cubic Hesitant Fuzzy Einstein Hybrid Weighted Averaging Operator and Its Application to Decision Making , 2018, Symmetry.

[11]  A. Shapiro,et al.  Fuzzy logic modifications of the Analytic Hierarchy Process , 2017 .

[12]  Juite Wang,et al.  A possibilistic decision model for new product supply chain design , 2007, Eur. J. Oper. Res..

[13]  Decui Liang,et al.  Three-Way Decisions with Interval-Valued Intuitionistic Fuzzy Decision-Theoretic Rough Sets in Group Decision-Making , 2018, Symmetry.

[14]  Imran Sarwar Bajwa,et al.  A Fuzzy Logic Based Intelligent System for Measuring Customer Loyalty and Decision Making , 2018, Symmetry.

[15]  Yafei Song,et al.  New Distance Measure for Atanassov's Intuitionistic Fuzzy Sets and Its Application in Decision Making , 2018, Symmetry.

[16]  Morteza Pakdin Amiri,et al.  Project selection for oil-fields development by using the AHP and fuzzy TOPSIS methods , 2010, Expert Syst. Appl..

[17]  Quanxin Sun,et al.  An Integrated Approach to Risk Assessment for Special Line Shunting Via Fuzzy Theory , 2018, Symmetry.

[18]  Oksana Kurakova,et al.  Scenarios of Applying of Game Theory in Development Projects of Underground Construction , 2016 .

[19]  Dariusz Walczak,et al.  Project rankings for participatory budget based on the fuzzy TOPSIS method , 2017, Eur. J. Oper. Res..

[20]  Sanjay Kumar,et al.  Improved Accuracy Function for Interval-Valued Intuitionistic Fuzzy Sets and Its Application to Multi–Attributes Group Decision Making , 2018, Cybern. Syst..

[21]  R. P. Mohanty,et al.  A fuzzy ANP-based approach to R&D project selection: A case study , 2005 .

[22]  E. Karsak,et al.  Fuzzy multi-criteria decision-making procedure for evaluating advanced manufacturing system investments , 2001 .

[23]  Chengdong Li,et al.  Shadowed Sets-Based Linguistic Term Modeling and Its Application in Multi-Attribute Decision-Making , 2018, Symmetry.

[24]  Xiaohong Zhang,et al.  Two Types of Intuitionistic Fuzzy Covering Rough Sets and an Application to Multiple Criteria Group Decision Making , 2018, Symmetry.

[25]  Ling Liu,et al.  Adoption of big data and analytics in mobile healthcare market: An economic perspective , 2017, Electron. Commer. Res. Appl..

[26]  Zhongfeng Qin Random fuzzy mean-absolute deviation models for portfolio optimization problem with hybrid uncertainty , 2017, Appl. Soft Comput..

[27]  Renato A. Krohling,et al.  Interval-valued Intuitionistic Fuzzy TODIM , 2014, ITQM.

[28]  Beyza Ahlatçioglu Ozkok,et al.  Fuzzy portfolio selection using fuzzy analytic hierarchy process , 2009, Inf. Sci..

[29]  Wenjun Ma,et al.  Multicriteria Decision Making with Cognitive Limitations: A DS/AHP‐Based Approach , 2017, Int. J. Intell. Syst..

[30]  Min Zhang,et al.  Novel Three-Way Decisions Models with Multi-Granulation Rough Intuitionistic Fuzzy Sets , 2018, Symmetry.

[31]  Daniel Kubek,et al.  Fuzzy AHP Application for Supporting Contractors' Bidding Decision , 2018, Symmetry.

[32]  Biswajit Sarkar,et al.  Periodic review fuzzy inventory model with variable lead time and fuzzy demand , 2017, Int. Trans. Oper. Res..

[33]  Hui Gao,et al.  Methods for Multiple Attribute Group Decision Making Based on Intuitionistic Fuzzy Dombi Hamy Mean Operators , 2018, Symmetry.

[34]  Shouzhen Zeng,et al.  Intuitionistic Fuzzy Multiple Attribute Decision-Making Model Based on Weighted Induced Distance Measure and Its Application to Investment Selection , 2018, Symmetry.

[35]  David Luviano Cruz,et al.  Multi-Agent Reinforcement Learning Using Linear Fuzzy Model Applied to Cooperative Mobile Robots , 2018, Symmetry.

[36]  Yan Zhang,et al.  Multi-criteria decision making method based on possibility degree of interval type-2 fuzzy number , 2013, Knowl. Based Syst..

[37]  Selin Soner Kara,et al.  Long term supplier selection using a combined fuzzy MCDM approach: A case study for a telecommunication company , 2009, Expert Syst. Appl..

[38]  Zuzana Komínková Oplatková,et al.  Assessing Commercial Viability of Technology Start-up Businesses in a Government Venture Capital under Intuitionistic Fuzzy Environment , 2017, Int. J. Fuzzy Syst..

[39]  Zhiming Zhang,et al.  Hesitant Fuzzy Multi-Criteria Group Decision Making with Unknown Weight Information , 2017, Int. J. Fuzzy Syst..

[40]  Wen-Jian Zhao,et al.  Triangular Fuzzy Number-Typed Fuzzy Cooperative Games and Their Application to Rural E-Commerce Regional Cooperation and Profit Sharing , 2018, Symmetry.

[41]  Pedro Albertos,et al.  FUZZY LOGIC MODELING OF SOCIAL BEHAVIOR , 1994 .

[42]  Lijun Wang,et al.  Quantified moving average strategy of crude oil futures market based on fuzzy logic rules and genetic algorithms , 2016 .

[43]  Mehtap Dursun,et al.  An Integrated Decision Framework for Material Selection Procedure: A Case Study in a Detergent Manufacturer , 2018, Symmetry.

[44]  Qiang Li,et al.  Novel Parameterized Distance Measures on Hesitant Fuzzy Sets with Credibility Degree and Their Application in Decision-Making , 2018, Symmetry.

[45]  Kuan Yew Wong,et al.  A Fuzzy Logic-Based Knowledge Management Performance Measurement System for SMEs , 2017, Cybern. Syst..

[46]  P. Sevastianov,et al.  MCDM in a fuzzy setting: Investment projects assessment application , 2006 .

[47]  Da Ruan,et al.  Measuring flexibility of computer integrated manufacturing systems using fuzzy cash flow analysis , 2004, Inf. Sci..