Satisfaction is relevant for decision makers (DM, Decision Makers). Satisfaction is the feeling produced in individuals by executing actions to satisfy their needs, for example, the payment of debts, jobs, or academic achievements, and the acquisition of goods or services. In the satisfaction literature, some theories model the satisfaction of individuals from job and customer approaches. However, considering personality elements to influence satisfaction and define preferences in strategies that optimize decision making provides the unique characteristics of a DM. These characteristics favor the scope of solutions closer to the satisfaction expectation. Satisfaction theories do not include specific elements of personality and preferences, so integrating these elements will offer more efficient decisions in computable models. In this work, a model of satisfaction with personality characteristics that influence the preferences of a DM is proposed. The proposed model is integrated into a preference-based optimizer that improves the decision-making process of a Virtual Decision Maker (VDM) in an optimization context. The optimization context addressed in this work is the product selection process within a food product shopping problem. An experimental design is proposed that compares two configurations that represent the cognitive part of an agent’s decision process to validate the operation of the proposed model in the context of optimization: (1) satisfaction, personality, and preferences, and (2) personality and preferences. The results show that considering satisfaction and personality in combination with preferences provides solutions closer to the interests of an individual, reflecting a more realistic behavior. Furthermore, this work demonstrates that it is possible to create a configurable model that allows adapting to different aptitudes and reflecting them in a computable model.

Nowadays enterprises face the necessity of taking many decisions related to their everyday activities. Usually, these decisions are made over real world problems whose solutions contribute to the achievement of desire results. The most common strategy followed to provide assistance in such situations is through the development of optimizations models that reflects the needs of an enterprise but also that incorporates particular preferences of the Decision Maker (DM) who is meant to select the best solution. According to the revised literature, the strategies that have been used so far to model preferences are based on goal attainment, utility functions, preference relations, outranking and fuzzy logic. Of particular interest are the outranking approaches which exploits outranking relations to give answer to Multi-objective Optimization Problems (MOPs); such approach has allowed the development of computable preference models, based on a predefined set of parameters, that reflect the interests of a DM. The most practical way that can be used to set the parameter values for that preference model is through Preference Disaggregation Methods (PDM), which are methods that based on a battery of examples provided by the DM elicits the entire set of parameters. Recently it has been observed that the preferences of a DM are strongly influenced by abstract aspects of his/her personality, e.g. his/her level of tolerance. In this direction, the personality and the emotional state are relevant elements that provide in some way an added value to these preferences, and they could produce more descriptive and approximate solutions to the reasoning of the individual. Hence, it is acceptable to think that the personality should influence the values of the parameters that define a specific preference model that is used to characterize a DM. This work analyzes the effects of personality over parameter values of preference models. It presents an architecture that takes as input aspects of a personality and use them to modify the parameter values of a preference model. The elements considered were ELECTRE III, a well-known model that takes into account the preferences of a DM, a proposed personality model which uses the most recurrent models of the theory of personality theory to provide a computable measure of the tolerance of an individual, and a proposed methodology to modify the parameters of ELECTRE III due to the personality. In this cognitive process, it was possible to identify the parameters where the personality can influence preferences. The case study presented in this research is a basic case of purchases in an online super market, where a virtual assistant interacts with the decision maker emulating their behavior when selecting products based on their preferences and personality, in order to facilitate the decision maker chooses the most convenient solution. The main objective in the proposed research is the study of the impact of the influence of personality on preferences within a decisional context. To prove the above, an experimental design is proposed, it simulates series of purchases based on lists of initial product requests to determine whether the purchases of the resulting products are close to the products originally requested.