SELECTION OF THE BEST CONSULTANT FOR SAP ERP PROJECT USING COMBINED AHP-IBA APPROACH

Abstract: In this paper we propose a combined AHP-IBA model for selecting the best SAP consultant for an SAP ERP project. The goal of the SAP Project Manager is to choose the best consultant, the one who is able to implement standard SAP functionalities with quality and on time.When making a decision on the basis of multiple criteria, the traditional Analytic Hierarchy Process (AHP) method does not take into account the fact that attributes may correlate, assuming that there are no dependencies between them. However, the dependencies of the attributes can often be used to model important knowledge for multiple criteria decision analysis. We propose an extension to the traditional AHP method by applying Interpolative realization of Boolean algebra (IBA), using AHP to determine the criteria weights, and IBA to model the logical interactions among criteria. The research conducted on ERP consultant selection suggests that the decision making process is modelled more accurately if logical interactions between attributes are modelled before applying AH

Adaptive fuzzy system for algorithmic trading : interpolative Boolean approach

Тема овог рада je адаптивни фази систем за алгоритамско трговање. Систем је развијен коришћењем интерполативног Буловог приступа фази моделовању, анализи података и управљању. Предложени приступ укључује интерполативне логичке моделе за фази препознавање ценовних образаца на тржишту, логички ДуПонт метод за аутоматизовану анализу профитабилности предузећа, интерполативни фази контролер за управљање трговањем и генетски алгоритам за обучавање интерполативног фази контролера ради откривања стратегија. Интерполативни Булов приступ, заснован на интерполативној Буловој алгебри, превазилази проблем неконзистентности фази логике. Конструисани адаптивни фази систем може самостално, из података, да открије успешне стратегије, примени их за алгоритамско трговање и адаптира у случају пада њихових перформанси. Успешност система тестирана је на подацима са америчког тржишта акција, међународног девизног тржишта и тржишта криптовалута.The topic of this thesis is adaptive fuzzy system for algorithmic trading. The system is developed using interpolative Boolean approach for fuzzy modeling, data analysis and control. The proposed approach includes interpolative logical models for fuzzy recognition of price patterns in market data, logical DuPont method for automated analysis of company’s profitability, interpolative fuzzy controller for trading and a genetic algorithm for extracting trading strategies by training interpolative fuzzy controller. Interpolative Boolean approach, based on interpolative Boolean agebra, solves the problem of fuzzy logic’s inconsistency with Boolean axioms. The proposed system can independently discover successful trading strategies from data, apply them for algorithmic trading and adapt in the case of performance deterioration. The system was tested on historical data from US equity, foreign exchange market and cryptocurrency market