Ispitivanje mogućnosti iznalaženja optimalne koncentracije evaporiranog mlijeka radi proizvodnje mlijeka u prahu na spray postrojenju, s osvrtom na Maillard-ov tip potamnjivanja

Autori su ispitivali utjecaj koncentracije evaporiranog mlijeka na kvalitetu mlijeka u prahu i pojavu Maillardove reakcije. Na osnovu rezultata provedenih fizičko-kemijskih i organoleptičkih ispitivanja zaključuju da je optimalno sušenje evaporiranog mlijeka sa 50 % s.t. U toku uskladištenja obranog i punomasnog (25 %) mlijeka u prahu do 90 dana na sobnoj temperaturi povećava se intenzitet Maillard-ove reakcije znatno brže, nego u mlijeku skladištenom kod 4 °C

Fuzzy Adaptive Parameter in the Dai–Liao Optimization Method Based on Neutrosophy

The impact of neutrosophy has increased rapidly in many areas of science and technology in recent years. Furthermore, numerous applications of the neutrosophic theory have become more usual. We aim to use neutrosophy to enhance Dai–Liao conjugate gradient (CG) iterative method. In particular, we suggest and explore a new neutrosophic logic system intended to compute the essential parameter t required in Dai–Liao CG iterations. Theoretical examination and numerical experiments signify the effectiveness of the introduced method for controlling t. By incorporation of the neutrosophy in the Dai–Liao conjugate gradient principle, we established novel Dai–Liao CG iterations for solving large-scale unconstrained optimization problems. Global convergence is proved under standard assumptions and with the use of the inexact line search. Finally, computational evidence shows the computational effectiveness of the proposed fuzzy neutrosophic Dai–Liao CG method

A New Grey Approach for Using SWARA and PIPRECIA Methods in a Group Decision-Making Environment

The environment in which the decision-making process takes place is often characterized by uncertainty and vagueness and, because of that, sometimes it is very hard to express the criteria weights with crisp numbers. Therefore, the application of the Grey System Theory, i.e., grey numbers, in this case, is very convenient when it comes to determination of the criteria weights with partially known information. Besides, the criteria weights have a significant role in the multiple criteria decision-making process. Many ordinary multiple criteria decision-making methods are adapted for using grey numbers, and this is the case in this article as well. A new grey extension of the certain multiple criteria decision-making methods for the determination of the criteria weights is proposed. Therefore, the article aims to propose a new extension of the Step-wise Weight Assessment Ratio Analysis (SWARA) and PIvot Pairwise Relative Criteria Importance Assessment (PIPRECIA) methods adapted for group decision-making. In the proposed approach, attitudes of decision-makers are transformed into grey group attitudes, which allows taking advantage of the benefit that grey numbers provide over crisp numbers. The main advantage of the proposed approach in relation to the use of crisp numbers is the ability to conduct different analyses, i.e., considering different scenarios, such as pessimistic, optimistic, and so on. By varying the value of the whitening coefficient, different weights of the criteria can be obtained, and it should be emphasized that this approach gives the same weights as in the case of crisp numbers when the whitening coefficient has a value of 0.5. In addition, in this approach, the grey number was formed based on the median value of collected responses because it better maintains the deviation from the normal distribution of the collected responses. The application of the proposed approach was considered through two numerical illustrations, based on which appropriate conclusions were drawn

Food Behavior Changes during the COVID-19 Pandemic: Statistical Analysis of Consumer Survey Data from Bosnia and Herzegovina

Bosnia and Herzegovina has responded to the COVID-19 pandemic by implementing quarantine and other social distancing measures. These measures, however, have mental, social, and economic consequences on diet and food behaviors. The Bosnian case is particularly pertinent since the country has one of the highest global mortality rates relative to its population. In addition, its health system is fragmented and under-resourced. Consequently, in this study, we analyze the effects of the COVID-19 pandemic on Bosnians’ behaviors relating to food. It is based on an online survey performed during October–November 2020 with 3133 adult respondents. The statistical analysis encompassed descriptive statistics (means, percentages, and frequencies), as well as cluster analysis. The results reveal that the pandemic transformed consumers’ shopping behaviors and food sourcing, reducing shopping frequency and increasing food bought on each trip. Furthermore, there was an increase in the consumption of local food items due to food safety concerns. Additionally, the pandemic improved the awareness of Bosnians towards food with a decrease in food waste. Regarding diets, Bosnians tried to have healthier diets during the pandemic. Therefore, COVID-19 might have opened a ‘window of opportunity’ to promote the shift towards more sustainable food consumption and lifestyles

Preparing for the Worst? Household Food Stockpiling during the Second Wave of COVID-19 in Serbia

Stockpiling and panic buying are significant components of crisis- and disaster-related consumption behaviors that have gained significant media coverage during the COVID-19 pandemic. This paper aims to analyze the features of stockpiling behavior during the second wave of COVID-19 in Serbia based on a structured online questionnaire. This study seeks to answer two questions. First, what factors triggered and affected stockpiling during the COVID-19 pandemic in Serbia? Second, how does stockpiling affect other food habits and diets? A total of 851 valid responses were received. The results highlight several features of the stockpiling behavior in Serbia. First, food stockpiling behavior is influenced by some sociodemographic variables such as gender and household composition. Second, stockpiling was fueled by several negative emotions such as fear, sadness, and depression. Third, the results confirm that stockpiling in Serbia was not triggered by supply shortages but rather by consumers’ concerns of obtaining enough food and rising food prices. Finally, food stockpiling was associated with some positive changes such as eating out less (e.g., restaurants/cafeteria), eating more with their family members, and cooking more food. Analyzing and comprehending consumer food stockpiling patterns during the COVID-19 pandemic may offer policymakers imperative information for adjusting supply and response strategies during future crises

An Exploration and Exploitation-Based Metaheuristic Approach for University Course Timetabling Problems

The university course timetable problem (UCTP) is known to be NP-hard, with solution complexity growing exponentially with the problem size. This paper introduces an algorithm that effectively tackles UCTPs by employing a combination of exploration and exploitation strategies. The algorithm comprises two main components. Firstly, it utilizes a genetic algorithm (GA) to explore the search space and discover a solution within the global optimum region. Secondly, it enhances the solution by exploiting the region using an iterated local search (ILS) algorithm. The algorithm is tested on two common variants of UCTP: the post-enrollment-based course timetable problem (PE-CTP) and the curriculum-based course timetable problem (CB-CTP). The computational results demonstrate that the proposed algorithm yields competitive outcomes when compared empirically against other existing algorithms. Furthermore, a t-test comparison with state-of-the-art algorithms is conducted. The experimental findings also highlight that the hybrid approach effectively overcomes the limitation of local optima, which is encountered when solely employing GA in conjunction with local search

Comparative Analysis of the Simple WISP and Some Prominent MCDM Methods: A Python Approach

This article presents a comparison of the results obtained using the newly proposed Simple Weighted Sum Product method and some prominent multiple criteria decision-making methods. For comparison, several analyses were performed using the Python programming language and its NumPy library. The comparison was also made on a real decision-making problem taken from the literature. The obtained results confirm the high correlation of the results obtained using the Simple Weighted Sum Product method and selected multiple criteria decision-making methods such as TOPSIS, SAW, ARAS, WASPAS, and CoCoSo, which confirms the usability of the Simple Weighted Sum Product method for solving multiple criteria decision-making problems

Comparative Analysis of the Simple WISP and Some Prominent MCDM Methods: A Python Approach

This article presents a comparison of the results obtained using the newly proposed Simple Weighted Sum Product method and some prominent multiple criteria decision-making methods. For comparison, several analyses were performed using the Python programming language and its NumPy library. The comparison was also made on a real decision-making problem taken from the literature. The obtained results confirm the high correlation of the results obtained using the Simple Weighted Sum Product method and selected multiple criteria decision-making methods such as TOPSIS, SAW, ARAS, WASPAS, and CoCoSo, which confirms the usability of the Simple Weighted Sum Product method for solving multiple criteria decision-making problems