Integration between Mathematical Programming and Fuzzy Logic to Optimize Consumers Behavior

What is mathematical fuzzy logic

The design of languages to tackle constraint satisfaction problems has a long history. Only more recently the reverse problem of introducing constraints as primitive constructs in programming languages has been addressed. A main task that the designers and implementers of such languages face is to use and adapt the concepts and algorithms from the extensive studies on constraints done in areas such as Mathematical Programming, Symbolic Computation, Artificial Intelligence, Program Verification and Computational Geometry. In this paper, we illustrate this task in a simple and yet important domain: linear arithmetic constraints. We show how one can design a querying system for sets of linear constraints by using basic concepts from logic programming and symbolic computation, as well as algorithms from linear programming and computational geometry. We conclude by reporting briefly on how notions of negation and canonical representation used in linear constraints can be generalized to account for cases in term algebras, symbolic computation, affine geometry, and elsewhere.

Paraconsistent logics are specially tailored to deal with inconsistency, while fuzzy logics primarily deal with graded truth and vagueness. In the last decade, mathematical fuzzy logic has been developed as a discipline studying formal many-valued systems arising from fuzzy set theory. In this paper we study to what extent dierent systems of fuzzy logic are paraconsistent, identifying which families of fuzzy logics satisfy interesting paraconsistency properties.

This paper presents a new approach to spatial change detection. It emphasizes the use of topology for the comprehension of grey scale images, through mathematical morphology and fuzzy logic. In conclusion, issues to the problem of change detection and integration of images into GIS are proposed.

Social media platforms such as TikTok and Instagram have significantly transformed how consumers interact with products and make purchasing decisions. This study aims to analyze the influence of social media usage and electronic word of mouth (e-WOM) on purchase decisions, with trust and consumer behavior serving as mediating variables. A quantitative, explanatory research design was employed. Data were collected from 164 respondents using purposive sampling and analyzed using Structural Equation Modeling–Partial Least Squares (SEM–PLS). The results show that social media usage has a significant effect on consumer behavior and directly influences purchase decisions. Meanwhile, e-WOM does not have a direct effect on purchase decisions but contributes significantly through the mediating roles of trust and consumer behavior. Trust plays an essential role in linking e-WOM to consumer behavioral responses. Among all the tested relationships, consumer behavior emerged as the strongest predictor of purchase decisions. These findings emphasize the importance of digital marketing strategies that foster trust and strengthen behavioral engagement. The study also reinforces the theoretical relevance of the Stimulus–Organism–Response (S-O-R) and Uses and Gratification (U&G) models in the context of social commerce. Future studies are encouraged to explore additional mediating factors such as emotional engagement or platform-specific characteristics to improve the model’s predictive strength.

The sorites paradox (interpreted as the paradox of small natural numbers) is analyzed using mathematical fuzzy logic. In the first part, we present an extension of BL-fuzzy logic by a new unary connective At of almost true and the crisp Peano arithmetic extended by a fuzzy predicate of feasibility. Then we give examples of possible semantics of At and examples of semantics of feasible numbers. In the second part, we present an analysis of the sorites paradox within fuzzy logic with evaluated syntax and show that under a very natural assumption we obtain a consistent fuzzy theory. Thus, sorites is not paradoxical at all.

Consumer behavior is perceived as an investment which does not yield results in the short run. The traditional economic theory of customer preferences is based on four main elements: customer income, the market price of goods, customer preferences, and behavioral assumption about the maximum of achievable benefits. Even though it sometimes might seem that equalizing energy consumption with behavior is not possible, it can often be described as consequences of behavior, such as turning off the lights or thermostat level reduction for saving power. Our paper demonstrates how the psychological concept of consumer behavior effects energy consumption. It provides recommendations about the incorporation of the idea of uncomplicated information availability for consumers taking into consideration their long-term habits. The novelty of this study is that psychological concept of consumer behavior effects energy consumption in each of the region, therefore, it is recommended to incorporate the idea of uncomplicated information availability for consumers taking into consideration long-term habits. The problem analyzed in the article is how consumer behavior influences energy consumption. The aim of the article is to analyze the consumer behavior in energy consumption. The objectives of the study are two-fold: i) to analyze the element of consumer behavior from the theoretical point of view, and ii) to investigate the patterns of energy consumption. The methods of the study are a logical and comparative analysis of literature, graphics, synthesis, and deduction. Our results and findings can be used by the stakeholders and policy-makers in preparing regional development economic policies and in designing the energy consumption strategies in the framework of the regional development. © Varanavicius V., Navikaite A., Bilan Yu., Strielkowski W. Text. 2017.

Constrained scheduling problems are quite common in project management, manufacturing, distribution, transportation, logistics, supply chain management, software engineering, and computer networks etc. The need to use integer and binary decision variables representing the allocation of different resources to many activities and numerous specific, universal and additional constraints on these decision variables are typical components of the resource-constrained scheduling problems (RCSPs) modeling. It is often necessary to model additional resources and constraints. For these reasons, models are becoming computationally demanding. This is particularly noticeable when methods of operations research (mathematical programing (MP), network programing, and dynamic programming) are used. On the other hand, most RCPSs can be easily modeled as instances of the constraint satisfaction problems (CSPs) and solved using constraint programming (CP) methods. In contrast to the MP-based environment, the CP-based environment methods deal well with binary constraints but worse in optimization. Therefore, the hybrid approach based on integration mathematical programming and constraint logic programming to optimization resource-constrained scheduling problems has been proposed. To evaluate the applicability and computational efficiency of the proposed approach and its implementation programming framework, the illustrative examples of optimization resource-constrained scheduling problems are implemented separately for mathematical programming and hybrid method.

The article explores the intricate dynamics of consumer behavior, particularly focusing on its implications for understanding purchasing decisions. It elucidates the multifaceted nature of consumer behavior, encompassing the acquisition, evaluation, utilization, and disposal of goods and services. The central emphasis lies in comprehending the behavior patterns of consumers during product selection to meet their needs and desires. Consumer behavior analysis becomes paramount for marketers, serving as a foundation for effective marketing strategies. This comprehensive study scrutinizes the myriad determinants influencing consumer behavior, including cultural, social, personal, and psychological factors. It underscores the pivotal role of understanding these determinants, despite their uncontrollable nature, in decoding the complexities of consumer behavior. Moreover, the article sheds light on the profound impact of lifestyle on consumer preferences and purchasing behaviors. It highlights the evolving nature of societal norms, allowing individuals in modern consumer societies to select products and services that mirror their identities. A substantial segment of the article delves into the evolving landscape of online shopping, specifically among rural consumers in Chengalpattu Town (Villages). It outlines the objectives of studying rural consumer behavior towards online shopping, aiming to analyze motivations, awareness levels, satisfaction, and product attribute influences on purchase decisions. The research methodology entails a descriptive survey employing structured questionnaires among rural consumers, emphasizing demographics and online shopping behavior. Findings illuminate demographic patterns, income levels, spending habits, and factors influencing online purchasing decisions among rural consumers. The article concludes by highlighting the advantages of online shopping, such as a diverse product range and cost-effectiveness, juxtaposed against barriers like psychological needs, trust issues, and limited internet access hindering the adoption of online shopping in rural areas. The provided suggestions aim to bridge these gaps by enhancing communication, education, trust-building, and infrastructure in rural markets, fostering a conducive environment for online commerce among rural consumers.

The purpose of this research is to examine and analyse the influence of consumer behaviour and innovation orientation on firm performance through business strategy, impacting the performance of MSMEs in Karanganyar, Indonesia. The study utilizes a quantitative approach, collecting data through questionnaires and semi-structured interviews with 80 owners of Mbangun Makhutoromo MSMEs Cluster in Karanganyar, Indonesia. The collection data were analysed using linear regression and path analysis with SPSS 24 software. The results indicate that consumer behaviour and innovation orientation significantly impact business strategy. Consumer behaviour has both direct and indirect effects on firm performance through business strategy. On the other hand, innovation orientation affects company performance indirectly through business strategy rather than directly. Enhancing company performance is more effective through direct consumer behaviour analysis. Additionally, well-formulated business strategies can leverage innovation orientation to achieve indirect improvement. For MSMEs to improve performance, a focus on understanding and analysing consumer behaviour is crucial. Business strategies should indirectly employ innovation orientation. This approach requires careful adaptation to environmental changes, consumer preferences, and market trends to ensure sustained business growth and competitiveness.

With the acceleration of big data applications and the development of informatization, the demand for personalized information has become a trend. More and more people are receiving and searching information according to their personal needs. In the era of big data, the styles of online platforms and consumers' shopping habits are diverse, and consumer data collection and behavior analysis are gradually expanding to more data sources. In the context of big data, it is of great significance to study the consumer behavior of sports consumers based on network integrated data. This article collects demographic data, shopping behavior, consumption intentions and other information through traditional questionnaire surveys and focus group interviews. Used to study and analyze the behavior of sports consumers, the data shows that the influence of sports consumption awareness accounts for 28.5%. This article compares traditional consumer behavior research models and sports data processing methods based on network-integrated data in the context of big data, and attempts to provide references for sports consumption.

The use of big data in consumer behavior analysis has emerged as a transformative force in the way businesses understand and predict customer actions. With the exponential growth of data from various touchpoints, including social media, transaction history, web browsing, and mobile devices, organizations are now able to analyze vast amounts of information to gain deeper insights into consumer preferences, motivations, and behaviors. This article explores the impact of big data on consumer behavior analysis, highlighting how it enables businesses to create more personalized experiences, optimize marketing strategies, and improve customer engagement. The study also examines the challenges and ethical concerns surrounding the use of big data in consumer research.

Due to globalization, competitive marketing strategies, and developments in communication technologies, analyzing consumer behaviors becomes much more complicated these days. Fundamentally, the most noteworthy factors that affect consumer behaviors are getting benefits, entertainment, feeling satisfied, and taking pleasure. Analyzing consumer behaviors and developing new strategies becomes crucial for companies during the COVID-19 period that turns daily life upside down. This study aims to investigate if there is a difference between hedonic and utilitarian consumption behaviors of participants who have a high- and low-level fear of COVID-19. The aims of former researches that were carried out up to the present were to find reasons and effects of hedonic consumption. Since this study aims to investigate hedonic and utilitarian consumption from the perspective of COVID-19 fear, which is an ultimate crisis, this study differs from other studies. An online questionnaire is selected as the research method of this study and the sample involves 548 (N=548) individuals. The research showed that there is a statistically significant difference among participants who have a high and low level of COVID-19 fear in terms of hedonic and hedonic and utilitarian consumption behaviors. Research results and limitations are discussed within the context of the literature.

The concept of decision support system for distribution center has been presented. Additional layer for information and functionality structures which enable to cooperate with ERP and optimization solvers has been described. The mathematical model for the detailed problem of palette allocation in distribution center and implementation of them have been used in two environments - mathematical programming and logic constraint programming.

Eid al-Fitr celebration is a significant moment in the culture and tradition of Muslim society, where the consumption of goods and services increases significantly. During this period, consumers tend to be more open to purchasing products related to the celebration's needs, such as clothing, food, and home decorations. This research aims to delve deeper into how consumer behavior towards MSME products during Eid al-Fitr celebration is influenced by social media interaction. The research method employed is a literature review with a qualitative approach utilizing descriptive analysis. Data used were gathered from academic sources indexed in Google Scholar, spanning from 2015 to 2024. The study's results indicate that in the current digital era, social media interaction plays a crucial role in influencing consumer behavior, especially during Eid al-Fitr celebration. MSMEs have significant opportunities to leverage social media to enhance product visibility and influence consumer purchasing decisions. Consumer behavior analysis suggests that factors such as content type, posting frequency, user interaction, and visual content quality greatly affect consumer interest. Moreover, brand trust and credibility also play a key role in influencing consumer behavior. Interaction between consumers and brands through comments, testimonials, or product reviews also has a significant impact on purchasing decisions. External factors such as market trends, economic conditions, and government policies also influence consumer behavior, necessitating MSMEs to have flexibility in adapting their marketing strategies.