# Review of Intelligent Methods and Their Potential Use towards a Smart Grid Negotiation Framework
## 3 Discussion
### Comprehensive Review of the Selected Studies
Furthermore, the evaluation of any package at any time during the intention negotiation phase by the negotiator in terms of overall performance is an extremely useful tool for the support of the negotiation. The proposed scoring system formation is resistant to new packages leading to a stable scoring system. FTOPSIS is computationally efficient and straightforward, while the AHP method elicits the importance of the issues rather than assigning them directly as usual. The iterative exchange of offers and counter-offers allows to reach an agreement which may be improved further during the post-agreement phase using the Nash and Kalai-Smorodinsky concepts on bargaining solutions. FTOPSIS in ill-structured negotiation problems is also analyzed in [28], as an applicable procedure to support certain tasks in negotiation, considering subjective and imprecise judgments of the negotiators. Again, FTOPSIS is used to evaluate the negotiation offers, to build the ranks of the compromise solutions, to construct the counteroffers, and to evaluate and compare the size of potential concessions. Also, it can support the improvisation of the achieved compromise by the negotiators by searching for the Pareto optimal and dominant solutions. The ability of FTOPSIS to deal with different types of values such as crisp, interval, Fuzzy, or linguistic. The FTOPSIS algorithm allows the transformation of data to a common domain of TFN and uses Fuzzy arithmetic to perform all required calculations. Again, the negotiation space for FTOPSIS calculations should be defined differently than the traditional approach, in order to avoid instabilities of the negotiation problems resulting in rank reversal. The initial negotiation space is broadened using TOPSIS-based maximum and minimum solutions, which include utopian packages that are unlikely to occur during the negotiation process, chosen on purpose by the negotiator. Nevertheless, this approach has drawbacks since the ideal and non-ideal solutions represented by max and min do not eliminate the instability problem entirely; extreme offers might still lie beyond the bounds of the feasible negotiation domain. Three approaches are suggested to deal with this problem, with the two using the TOPSIS-specific notion of distance measuring while the third one introduces the notion of deviation, shifting the viewpoint from which offers are assessed. These methodologies are not interchangeable nor universally applicable to any negotiation scenario. Their suitability hinges on the negotiator's philosophy regarding offer evaluation and the robustness of their reference points, which sets the authors' future research goals as the building of a negotiation support software and undertaking a series of experiments to determine the contextual circumstances under which each of the proposed approaches is chosen by negotiators and the underlying reasons behind these choices. In [36], a method named IFIRP multi-criteria method which belongs to the class of algorithms based on reference points such as TOPSIS is proposed; negotiation offers are assessed and ordered using an intuitionistic Fuzzy framework. Under the assumption that package selection operates within a bipolar framework, taking into account both their advantages and disadvantages across specific issues. Options' evaluation can be represented by membership and non-membership grades, respectively. Moreover, an intuitionistic Fuzzy method is proposed to apply to the Multi-Criteria Decision Making (MCDM) problem, based on [PERSON]'s concept of reference point to alternatives' ranking. This method is also applied to evaluate negotiation offers. The IFIRP method offers the advantage of accommodating natural language, subjective considerations, and the handling of imprecision or uncertainties in the evaluation of negotiation offers. It presents a potential alternative multi-criteria approach for supporting negotiators, assisting them in mitigating biases and heuristics during the evaluation of negotiation offers.