Pessimistic Strategy Research Articles

A Bilevel Approach to the Facility Location Problem with Customer Preferences Under a Mill Pricing Policy

This paper addresses the facility location problem under a mill pricing policy, integrating customers’ behavior through the concept of preferences. The problem is modeled as a bilevel optimization problem, where the existence of ties in customers’ preferences can lead to an ill-posed bilevel problem due to the possible existence of multiple optima to the lower-level problem. As the commonly employed optimistic and pessimistic strategies are inadequate for this problem, a specific approach is proposed bearing in mind the customers’ rational behavior. In this work, we propose a novel formulation of the problem as a bilevel model in which each customer faces a lexicographic biobjective problem in which the preference is maximized and the total cost of accessing the selected facility is minimized. This allows for a more accurate representation of customer preferences and the resulting decisions regarding facility location and pricing. To address the complexities of this model, we apply duality theory to the lower-level problems and, ultimately, reformulate the bilevel problem as a single-level mixed-integer optimization problem. This reformulation incorporates big-M constants, for which we provide valid bounds to ensure computational tractability and solution quality. The computational study conducted allows us to assess, on the one hand, the effectiveness of the proposed reformulation to address the bilevel model and, on the other hand, the impact of the length of the customer preference lists and fixed opening cost for facilities on the computational time and the optimal solution.

The Role of the Law in Critical Theory: An Engagement with Hardt and Negri’s Commonwealth

AbstractThis paper discusses the role of Law and Legal Thinking in Critical Theory with specific reference to the arguments that Michael Hardt and Antonio Negri offer in their book Commonwealth. The core idea is that Critical Theory is no less radical, but much more concrete, when it is performing not only an external, but also an internal critique of the Law. It shows that the role of the law in critical theory emerges as a problem when the latter claims that ‘there is no outside’ and that ‘the legal base of the system structures our lives.’ It then discusses optimistic and pessimistic strategies to overcome the problem, and argue for a demanding strategy which consist in articulating the external and the internal critique of the law. To make this point, the paper goes back to the epistemic context in which critical attitudes are deployed (the ‘Conflict of the Faculties’), describes the four theoretical moves constitutive of the historical moment in which, at the end of the 18th Century, modern law as we know it was conceived of and founded; and sketches the key moments of the history of the internal critique of the law. It then illustrates the demanding strategy with examples taken from the field of Intellectual Property, and concludes that the Law is malleable and open enough to allow the thinking and practicing of radical alternatives from within the legal system and also that alternatives spoken in the language of the law are no less radical, but certainly, more concrete than others.

Three-way decision-making methods with multi-intuitionistic β-neighborhood-based multiattribute group decision-making problems

Multiattribute group decision-making (MAGDM) is a decision analysis method used to address decision-making problems that have multiple attributes and multiple decision alternatives. It is generally believed that multigranulation rough sets (MGRSs) are a twofold scheme to solve MAGDM problems. Thus, in this paper, we aim to generalize MGRSs and decision-theoretic rough sets (DTRSs) to intuitionistic fuzzy β-covering (IFβC) information systems and propose a novel MAGDM method to handle decision-making problems, which not only deepens the cognition of the three-way decision (3WD) model but also expands its application in decision-making problems. The paper first introduces a novel conditional probability using the ideal positive degree of intuitionistic fuzzy numbers (IFNs) and then investigates its properties. Second, in the IFβC environment, we utilize the proposed conditional probabilities to construct two types of multigranulation decision-theoretic rough set (MGDTRS) models, an optimistic strategy and a pessimistic strategy, discuss their theoretical properties and explore the relationship between the two strategies. Third, a novel MAGDM method for multi-intuitionistic β-neighborhoods is established in accordance with the proposed MGDTRS model. We also establish an algorithm for the proposed MAGDM method. Fourth, we apply the proposed method to address several MAGDM problems. By conducting comparative analysis with existing methods, we demonstrate the effectiveness of the proposed method and discuss the advantages and limitations of the proposed method. Furthermore, we conduct extensive parameter experimentation analysis on the proposed method from different perspectives. The experimental results demonstrate the stability and effectiveness of our proposed method.

Improved efficiency assessment in network DEA through interval data analysis: An empirical study in agriculture

Conventional Network Data Envelopment Analysis (NDEA) models often make an assumption of data precision, which frequently does not align with the realities of many real-world scenarios. When dealing with ambiguous data, whether it involves input, output, or intermediate products represented as bounded or ordinal data, the accurate assessment of efficiency scores poses a significant challenge. This study addresses the crucial issue of handling interval data within NDEA structures by introducing an innovative methodology that integrates both optimistic and pessimistic strategies. Our proposed methodology goes beyond the mere determination of upper and lower bounds for efficiency scores; it also incorporates target-setting and improvement approaches. Through the calculation of interval efficiency for each decision-making unit (DMU), our approach offers a comprehensive framework for efficiency classification. To underscore the effectiveness of this methodology, the study presents empirical evidence through a case study in the agriculture industry. The results not only showcase the advantages of our proposed methodology but also emphasize its potential for practical application in diverse and complex real-world contexts.

NEGATIVE POLITENESS STRATEGIES IN BATAM COMPANIES' ENGLISH BUSINESS LETTER

This research aimed to the being pessimistic politeness strategy in the text of business letter from several Companies in Batam, Riau Island, Indonesia. This study includes multiple companies, with three companies chosen at random. Brown and Levinson (1987) define negative politeness methods as displaying restraint, formality, and distance. A descriptive qualitative method was used in analyzing the data because it would be explained by words, phrases, and sentences. The researcher employed the Sudaryanto (2015) observational method to obtain data. Brown and Levinson identified five negative politeness methods; however, in this study, the researchers focused solely on the pessimistic strategy. Pragmatics identity method was applied in analyzing the data. it was found that there were nine strategies of being pessimist politeness in the text of business letters. There are 2 data of being pessimistic in Letter 1 by PT. Vancouver Manufacturing Company, 4 data of being pessimistic in the Letter 2 by ABC Software Company, and 3 data of being pessimistic in Letter 3 by Mass Airlines Company.

Reliability evaluation of complete graph-based recursive networks

With the development of cloud computing and high-performance computing technologies, the scales of data center networks and interconnection networks become more and more large. As a result, the reliability evaluation of the two kinds of networks is very important. And most scholars study the reliability of specific networks. In this paper, we put forward a kind of complete graph-based recursive networks (short as CGRNs) which includes data center networks—DCell and generalized DCell, as well as the interconnection network dragonfly, etc. Then we further investigate the reliability of such networks—the connectivity, the diagnosability under the pessimistic diagnosis strategy based on the PMC model, g-restrict connectivity, and the g-good-neighbor conditional diagnosabilities under the PMC model and the MM⁎ model. As applications, previous results of DCell networks can be directly obtained and new results on the connectivity, diagnosability under the pessimistic strategy diagnosis based on the PMC model, g-restrict connectivity, and the g-good-neighbor conditional diagnosabilities under the PMC model and the MM⁎ model of networks (such as generalized DCell networks and dragonfly networks), are derived. Even these reliability results can be obtained for some other networks different from DCell networks, generalized DCell networks, and dragonfly networks. In addition, it can be seen that the diagnosability under the pessimistic diagnosis strategy based on the PMC model, the g-restrict connectivity, and the g-good-neighbor conditional diagnosabilities under the PMC model and the MM⁎ model of Gr are about 2 times of its diagnosability, g+1 times of its connectivity, and g+1 times of its diagnosability, respectively.

Three-way Preference Completion via Preference Graph

With the personal partial rankings from agents over a subset of alternatives, the goal of preference completion is to infer the agent’s personalized preference over all alternatives including those the agent has not yet handled from uncertain preference of third parties. By combining the partial rankings of the target agent and the partial rankings from third parties to settle some disagreement with three-way preference completion, which includes a general strategy, an optimal strategy, and a pessimistic strategy, it forms the weighted preference graph. Technically, to settle the disagreement and obtain the completed preference of the target agent in the weighted preference graph, maximum likelihood estimation (MLE) under Mallows is proposed and validated theoretically by removing edges with the minimum weight in the weighted preference graph. However, it is not easy to locate the edges with the minimum weight efficiently in a big graph. Hence, an optimal MLE algorithm and three greedy MLE algorithms are proposed to process the MLE. Furthermore, these proposed algorithms are experimentally validated and compared with each other by both the synthetic dataset and the Flixter dataset.

A stochastic-interval model for optimal scheduling of PV-assisted multi-mode charging stations

Nowadays, photovoltaic-assisted charging stations are becoming popular worldwide because its capacity to accommodate more clean energy, reduce carbon emissions, alleviate peak charging loads and provide wider charging infrastructures worldwide. When these infrastructures are operated locally, energy management becomes a challenge due to the large number and heterogeneity of uncertainties involved. This aspect is especially noticeable in the case of charging demand, which is difficult to predict. To address this issue, this paper develops a novel stochastic-interval model for optimal scheduling of multi-mode photovoltaic-assisted charging stations. The developed model uses interval formulation to model uncertainties from photovoltaic generation and energy price, while a comprehensive stochastic model is proposed for charging demand. The developed optimal scheduling model is solved using a developed iterative model, which avoids using interval arithmetic explicitly. This methodology encompasses two Mixed-integer linear programming problems and one Quadratic-programming problem, that can be efficiently addressed by conventional solvers, and allows adopting optimistic or pessimistic strategies. A case study is presented on a benchmark mid-size charging station to validate the developed model. As a sake of example, the system profit grows by 9% and decreases by 3% adopting optimistic and pessimistic point of view, respectively. Likewise, total PV generation increases by 150 kWh/day and reduces by 50 kWh/day. Similar conclusions are extracted for other parameters like monetary balances, PV peak power or satisfied EV demand.

Pessimistic Strategy in Negative Politeness Study in Thor: Ragnarok Movie

Good communication is the basis of a good relationship. In achieving the appropriate goals, responses, and reciprocities of speech, people tend to apply the value of decency. The pessimistic strategy of negative politeness is analyzed in this study. The data used in this study is taken from the Thor: Ragnarok Movie. This study analyzes the type of pessimistic strategy of negative politeness, such as negative, subjunctive, and remote-possibility makers. Besides, this study analyzed the factors that influence the character who used the pessimistic strategy. Factors are relative force, social distance, and level of imposition. The analysis of types and factors is based on the courtesy theory of Brown and Levinson's book "Politeness Some Universals in Language Usage" (1987). The result showed that all of the three types of pessimistic strategy in negative politeness is found in Thor: Ragnarok Movie. The negative was found in the use of tag questions. The subjunctive could be found in the use of the would, should, and the use of the IF clause. The remote-possibility makers was found in the use of word hope, supposed, though, and perhaps. The most type pessimistic strategy found in this data is the use of the subjunctive and the most factor which influences the characters is the size of imposition.

A regret theory-based three-way decision approach with three strategies

Breast cancer is a malignant tumor that seriously threatens women’s health. Although classic multi-attribute decision-making (MADM) techniques can handle this kind of medical problem, a decision-maker (DM) can only collect sample data under various indicators for result ranking and analysis. The three-way decision (3WD) theory further supplements a classification scheme. In addition, a DM’s own limited rationality and personality traits have a strong impact on decision-making results. By using a dominance-based rough set approach (DRSA), a new 3WD method based on the regret theory (RT) with optimistic, neutral and pessimistic strategies (3WD-RT-OEP) is constructed in a fuzzy environment, so as to prevent diseases in advance and improve the survival rate of patients. First, attribute weights are calculated based on the similarity between the defined attributes of dominance classes, and a new method for calculating conditional probabilities is proposed to enhance the objectivity of the method by the similarity between object dominance classes and decision classes. Second, the score functions of three strategies are proposed by considering regret and rejoicing values in RT, and specific steps and algorithms of the 3WD-RT-OEP method are given as well. Finally, the validity and rationality of the constructed method are proved by experimental analysis with the support of case studies and supplementary data sets.

КОНСОЛИДАЦИОННЫЙ ПОТЕНЦИАЛ СИМВОЛОВ РОССИИ БУДУЩЕГО В СОЗНАНИИ РОССИЙСКОЙ МОЛОДЕЖИ: ИНСТРУМЕНТАЛЬНАЯ КОГНИТИВИСТИКА

The article analyzes the results of the symbolic construction of the image of the future of Russian youth, taking into account modern communication channels and the imperative of digital development. The purpose of the work is to present, on the basis of empirical information, the process of integration by actors of basic values, symbols, meanings into the consciousness of Russian youth. The product of this process is the image-construct of the future of Russia. The result of the work was the description of a number of symbols, which are divided into the archetypes of "consent", "trust" and "pride", as a symbolic basis for the positive perception of the image of the future Russian Federation by youth. In addition, empirical analysis allowed the authors to divide youth into the following clusters, which are based on behavioral strategies. These are: 1) representatives of illusory-optimistic groups, 2) carriers of optimistic and realistic pragmatism, 3) sympathizers of fatalistic and pessimistic strategies. Within the framework of projective cognitive science, the authors used modern methods and technologies for working with sources, including cybermetrics, which made it possible to take into account the factor of social media flows in youth influencing. The practical significance of the study - the results of empirical analysis can become experienced practitioners in the activities of authorities and administration in conducting systemic educational work among the youth in terms of meaning production and symbolic youth policy.

Optimal Look-Ahead Strategic Bidding/Offering of Integrated Renewable Power Plants and CAES With Stochastic-Robust Approach

Today, due to the high penetration of renewable energy resources and restructuring of power systems, photovoltaic power plants (PVPPs) and wind power plants (WPPs) as renewable power plants (RPPs) can participate in the electricity markets. However, the intermittent power generation of RPPs may be challenging for the owners of these power plants. In order to mitigate the unpredictable and intermittent power generation of RPPs, energy storage systems like compressed air energy storage (CAES) can be an appropriate solution. In this paper, the optimal day-ahead and look-ahead strategic offering and bidding of integrated RPPs and CAES in the electricity market are investigated. Also, a stochastic-robust approach is proposed for modeling renewable generation and electricity price uncertainty. The proposed mixed-integer linear program (MILP) is formulated in GAMS software under the CPLEX solver. Three case studies are investigated to validate the proposed method. According to numerical results, in the optimistic strategy, the coordinator of RPPs and CAES has more opportunities to participate in the electricity market. But in the pessimistic strategy, due to low electricity market (EM) prices, the coordinator has no more tendency to participate in the electricity market compared to the optimistic strategy.

A three-way decision method based on fuzzy rough set models under incomplete environments

The paper primarily explores the applicability of three-way decision (TWD) to multi-attribute decision-making (MADM), and establishes a new three-way multi-attribute decision-making (TW-MADM) method under an incomplete environment. For the sake of making rational decisions for MADM problems with fuzzy values, fuzzy rough set models are first utilized to investigate a new TWD model. By taking into account the hesitation degree of each evaluation value, a data-driven method to determine the relative loss functions is presented. Moreover, a new conditional probability calculation method is put forth via the information granularity of each object. In light of the above statement, a novel TWD model with three strategies is proposed. Afterwards, the arithmetic mean method is adopted for patching the lost data to effectively address incomplete MADM problems. Given the uncertainty of the patched data and real data, a new TW-MADM method as well as a corresponding MADM algorithm is designed. By several comparative analysis and experimental analysis, the feasibility, effectiveness, superiority and stability of the method are demonstrated. In addition, the results show that the presented method with optimistic strategies is more viable and stable than the method with compromise and pessimistic strategies.

Portfolio optimization of bank credits with interval returns: Empirical evidence from Iran

Bank credit is one of the main sources of spending on productivity and economic services. However, because of the limitations in its amount, accurate planning is essential to optimize its allocation to applicants. Despite the total volume of credits allocated to the agricultural sector, as well as the large number of applicants and sub-sectors applying for these facilities, there is still no clear pattern for the optimal allocation of agricultural bank credits in Iran. It is bank managers who must decide on the distribution of financial capital in a competitive environment. Based on this fact, the paper investigates the optimum portfolio composition of the Agricultural Bank credits in accordance with optimistic, pessimistic, and collaborative strategies by using an interval non-linear multi-objective programming model and considering three different states in determining the rate of return using a genetic algorithm. The results showed that the current pattern of the distribution of bank credits is estimated as different from the optimal one. In the optimum patterns estimated in all states, the agriculture, agricultural services, animal husbandry, aviculture and greenhouses sections were assigned the largest shares in their optimum portfolio combination. Managers can choose their desired model according to three studied strategies and depending on the importance, different estimates of return, and risk of each of them.

Robust optimization strategy for intelligent parking lot of electric vehicles

In this paper the concept of intelligent parking lot (IPL) is proposed to csolve various challenges of electric vehicles (EVs) integration into the power system. Robust optimization approach is proposed to model the power price uncertainty and obtain the optimal bidding curves of IPL for each hour in order to submit to the power market. Using the provided optimal bidding curves, system operator can get required power to satisfy demand of the system with economical price under power price uncertainty. Optimal scheduling of each component of the system is studied in three different strategies as optimistic, deterministic, and pessimistic to consider all possible cases raised by the power price uncertainty. Each strategy has been solved in two cases as with and without demand response program (DRP). The applied DRP has reduced system operating cost through flattening the load curve. By comparing ROA results with the deterministic case, the total operating cost of the system is decreased from $1029 to $995 about 17.85% decrease while in pessimistic strategy, it is increased from $1209 to $1333 indicating about 9.85% increase. The problem has been solved using GAMS optimization software with the CPLEX solver.

A Novel Three-Way Investment Decisions Based on Decision-Theoretic Rough Sets with Hesitant Fuzzy Information

As a classic model of three-way decisions, the decision-theoretic rough sets (DTRSs) have been adopted to help make profit-based investment decisions. However, there is epistemic uncertainty in the assessment of investment projects, hence the hesitant fuzzy sets (HFSs) are appropriate tool for characterizing the revenue functions and cost functions. To get a more reasonable result in the three-way investment decisions, we introduce HFSs to DTRSs and explore a new three-way investment decision model. Firstly, we take into account the revenue and cost of DTRSs with hesitant fuzzy elements and propose a hesitant fuzzy decision-theoretic rough sets (HFDTRSs) model. Then, we calculate the revenue functions and cost functions by aggregating hesitant fuzzy elements with the Bayesian decision procedure. Considering the differences in the personalities and attitudes of decision-makers, we propose optimistic strategy and pessimistic strategy to aggregate revenue functions and cost functions. Finally, based on the score of profit maximization, we make three-way investment decisions. A case study of coal investment was used to demonstrate the proposed methods.

Developing FIA5 to FSTPR25 for modeling spatio-temporal relevancy in context-aware wayfinding systems

Wayfinding or leading a moving user from an origin to a target is one of the main research focuses in urban context-aware systems. Space and time are two dominant properties of the context-aware wayfinding process and spatio-temporal relevancy between the fixed urban entities and the moving users determine whether an entity is related to the moving user or not. This paper specifically concentrates on the development of customized fuzzy interval algebra (FIA5) for detecting spatio-temporally relevant contexts to the user. This paper integrates fuzzy spatial and temporal intervals and customizes the spatio-temporal relations between the new data models—called fuzzy spatio temporal prism relevancy (FSTPR25) model-based on Allen’s fuzzy multi interval algebra. In this implementation, the FSTPR25 helps the tourist to find his/her preferred areas that are spatio-temporally relevant with two optimistic and pessimistic strategies. The experimental results in a scenario of tourist navigation are evaluated with respect to the accuracy of the model in 450 iterations of the algorithm in 15 different routes based on the statistical quantifiers in Tehran, Iran. The evaluation process demonstrated the high accuracy and user satisfaction of the optimistic strategy in real-world applications.

A multi-objective model to optimal selection of safety measures in oil and gas facilities

Optimal selection of safety measures (SMs) is a challenging task for safety managers due to its importance, complexity, and incapability of traditional approaches in considering all the aspects of SMs optimal selection. Sophisticated mathematical models can be used to overcome the limitations of traditional approaches. However, setting the objective functions while considering their priorities as well as possible synergistic effects of the SMs on the hazards are still among the main concerns in the development and application of mathematical models.The present study is aimed at developing a methodology to optimize the SMs selection while addressing the aforementioned challenges and considering both the budget and the risks. To do so, first the Pareto set of the solutions is obtained by NSGA-II technique - a multi-objective genetic algorithm technique - where a lexicographic model is used to select the optimal solution from the Pareto set based on the priority of the objective functions. A pessimistic strategy is used to account for the synergistic effects and the overlaps between the selected SMs.Two mathematical models are developed to represent different policies in optimal SMs selection in a gas wellhead and surface facility. The results show a notable difference between the two policies, indicating the importance of setting proper objective functions in multi-objective optimization problems. The results also show that the methodology is able to effectively satisfy different safety management policies and constraints with no need for much extra information except the cost and impact of SMs on the hazards’ risk.

TWO METHODS FOR CONSTRUCTION OF SUBOPTIMISTIC AND SUBPESSIMISTIC SOLUTIONS OF THE INTERVAL PROBLEM OF MIXED-BOOLEAN PROGRAMMING

Context. The interval problem of mixed Boolean programming having numerous economic applications is considered. The object of the study was a model of the integer programming. Objective. Development of methods for constructing suboptimistic and subpessimistic solutions of the mixed Boolean programming interval problem. Two methods for constructing suboptimistic and subpessimistic solutions of mixed Boolean programming problems with interval initial data are introduced. These methods are based on some economic interpretation of the model considered. Method. Two methods for constructing suboptimistic and subpessimistic solutions of mixed Boolean programming problems with interval initial data are introduced. These methods are based on some economic interpretation of the considered model. In the first method a criterion of selecting unknowns for assigning values, which is based on the principle of profit maximum for each unit of expenditure is introduced. Since the coefficients of the problem are intervals, two strategies are chosen: optimistic and pessimistic. In the optimistic strategy, the idea of choosing unknowns is used, which corresponds to the maximum ratio of the corresponding maximum profit to the minimum expenditure. And in the pessimistic strategy, the idea of maximum ratio of the minimum profit to the maximum expenditure is used. In the second method, the concept of a non-linearly increasing penalty (price) for using a unit of the remaining resources is introduced, that on the right side is bounded. Taking into account the principles of the above first and second methods, using this concept of penalty (price), methods for constructing suboptimistic and subpessimistic solutions have been developed. Results. The algorithms for constructing suboptimistic and subpessimistic solutions to the interval problem of mixed Boolean programming are developed. Conclusions. A software package was developed for constructing suboptimistic and subpessimistic solutions to the interval problem of mixed Boolean programming. A number of computational experiments have been carried out over random problems of various dimensions.

Diagnosability of the exchanged crossed cube

ABSTRACTThe -dimensional exchanged crossed cube combines the strong points of the exchanged hypercube and the crossed cube. It has been proven that has more attractive properties than other variations of the basic hypercube in terms of the smaller diameter, fewer edges, and lower cost factor. In this paper, we study the diagnosability of under the pessimistic diagnosis strategy based on two diagnostic models: the PMC model and the MM* model. And we obtain the following results: if , the diagnosability of the are both under the pessimistic diagnosis strategy based on the two models.