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.
In the purchase of products, a warehouse is an integral part between producers and customers, where the order picking is one of several operations involved. This chapter highlights the prioritization of the selection of the elements that make up an order based on the influence of the customer's personality on their preferences in order to choose the alternatives of the order. For this purpose, two approaches of personality theories are integrated in order to model the influence of personality as a factor that influences the parameter values of preference models based on outranking relations. The application case deals with an online supermarket using an intelligent virtual agent as the assistant that receives the order, who emulates the personality and preferences of the customer, selecting and delivering the best order. This chapter will emulate the behavior of decision makers, showing the impact of personality on preferences and will analyze its range of applications in problems related to the order picking.
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