multilevel programming is a mathematical programming problem with hierarchical structure. A typical feature of multilevel programming is that the upper level exhibits a priority over the lower level. However, the solu...
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multilevel programming is a mathematical programming problem with hierarchical structure. A typical feature of multilevel programming is that the upper level exhibits a priority over the lower level. However, the solutions obtained by most existing programming methods either violate this rule or ignore the participants' desire for a win-win outcome. The objective of this study is to propose new multilevel programming approaches for obtaining desirable solutions. First, three types of membership functions in neutrosophic set are defined to comprehensively describe fuzzy cognition of decision makers. Then, considering dissimilar intentions of experts, three different interactive approaches are proposed to solve multilevel programming problems. To demonstrate the feasibility of the proposed approaches, a case of pricing decision-making of data products is investigated and the impacts of four key parameters are discussed. Finally, several numerical examples are studied by using the proposed approaches and other existing methods. Two evaluation indexes, the equilibrium coefficient and distance measure, are utilized to appraise the performance of the developed programming methods. The results demonstrate that the proposed approaches can obtain sound solutions which obey the rule of multilevel programming, realize the mutual benefits of participants, and can provide guidelines for the pricing of satellite image data products.
All-inorganic halide perovskites CsPbX3 (X = Cl, Br or I) have transpired to be utilized in several optoelectronic devices owing to their multifaceted optical and electrical features and superior thermal stability as ...
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All-inorganic halide perovskites CsPbX3 (X = Cl, Br or I) have transpired to be utilized in several optoelectronic devices owing to their multifaceted optical and electrical features and superior thermal stability as compared to other organic-inorganic hybrid perovskites. Herein, a bipolar resistive switching (RS) characteristic of the CsPbX3 cube in Al/CsPbClxBr3-x (x = 3, 1.5, 0)/ITO/PET configuration is reported with a low operating voltage. Among all the fabricated memory devices, the CsPbBr3-based system presents the most pronounced RS characteristics such as no initial forming process, reproducibility, uniform switching, and long retention time with a high on/off ratio. By a subtle control over current compliance and stopping voltage, the multilevel data storage capabilities are also observed in flexible memory devices. Owing to the increasing demand of flexible electronics, current-voltage characteristics are further carried out under different bending diameters to access the mechanical stability and electrical reliability of the perovskite-based memory device. No discernible difference is observed in the low-resistance state and high-resistance state current under flat and bending conditions. Additionally, as fabricated devices show an enhanced RS effect where the resistance can be controlled both by electrical field and light illumination, this study also explores the data encoding process by using certain light irradiance during the SET process. The registered RS behavior is elucidated with a model of the creation and annihilation of a conductive multifilament that originated from the migration of halide ions and their corresponding vacancies in halide perovskite layers. This study will pave the way for the utilization of inorganic-halide perovskites with different nanoforms in low-power consumption nonvolatile memory of future wearable electronic gadgets.
A number of uncertain multilevel programming models have been proposed and applied to decentralized decision-making problems. It is assumed that the models of uncertain multilevel problems involve uncertain variables....
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This paper presents a two-phase intuitionistic fuzzy goal programming (two-phase IFGP) algorithm to solve Multi-Objective multilevel programming (MO-MLP) problems. The coefficient of each objective and constraint func...
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This paper presents a two-phase intuitionistic fuzzy goal programming (two-phase IFGP) algorithm to solve Multi-Objective multilevel programming (MO-MLP) problems. The coefficient of each objective and constraint function is assumed to be triangular intuitionistic fuzzy parameters and the crisp MO-MLP problems are obtained using the accuracy function method. To avoid decision lock, the top levels set tolerance limits for decision variables to control the lower levels. The problem is modeled in the intuitionistic fuzzy environment using membership and non-membership functions for each objective function at all levels and decision variables controlled by the top levels. Then, we proposed an IFGP algorithm to achieve the highest degree of each membership and non-membership goal by minimizing unwanted deviational variables and generating compensatory solutions for all decision-makers at all levels. Moreover, in the proposed approach, two-phase IFGP is modeled to yield a compromise solution that satisfies both the MN-Pareto optimal solution and the Pareto optimal solution at each level. Also, verification of the proposed method is discussed with numerical examples.
multilevel programming appears in many decision-making situations. Investigation of the main properties of quasiconcave multilevel programming (QCMP) problems, to date, is limited to bilevel programming (only two leve...
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multilevel programming appears in many decision-making situations. Investigation of the main properties of quasiconcave multilevel programming (QCMP) problems, to date, is limited to bilevel programming (only two levels). In this paper, first, we present an extension of the properties of quasiconcave bilevel programming (QCBP) problems for the case when three levels exist. Then, by induction on n (the number of levels), we prove the existence of an extreme point of the polyhedral constraint region that solves the QCMP problem under given conditions. Ultimately, a number of numerical examples are illustrated to verify the results.
multilevel programming is developed for modeling decentralized decision-making processes. For different management requirements and risk tolerances of different-level decision-makers, the decision-making criteria appl...
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multilevel programming is developed for modeling decentralized decision-making processes. For different management requirements and risk tolerances of different-level decision-makers, the decision-making criteria applied in different levels cannot be always the same. In this paper, a hybrid multilevel programming model with uncertain random parameters based on expected value model (EVM) and dependent-chance programming (DCP), named as EVM-DCP hybrid multilevel programming, is proposed. The corresponding concepts of Nash equilibrium and Stackelberg-Nash equilibrium are given. For some special case, an equivalent crisp mathematical programming is proposed. An approach integrating uncertain random simulations, Nash equilibrium searching approach and genetic algorithm is designed. Finally, a numerical experiment of uncertain random supply chain pricing decision problem is given.
multilevel programming problems model a decision-making process with a hierarchy structure. Traditional solution methods including vertex enumeration algorithms and penalty function methods are not only inefficient,to...
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multilevel programming problems model a decision-making process with a hierarchy structure. Traditional solution methods including vertex enumeration algorithms and penalty function methods are not only inefficient,to obtain the solution of the multilevel programming problems, but also lead to a paradox that the follower's decision power dominates the leader's. In this paper, both multilevel programming and intuitionistic fuzzy set are used to model problems in hierarchy expert and intelligent systems. We first present a score function to objectively depict the satisfactory degrees of decision makers by virtue of the intuitionistic fuzzy set for solving multilevel programming problems. Then we develop three optimization models and three interactive intuitionistic fuzzy methods to consider different satisfactory solutions for the requirements of expert decision makers. Furthermore, a new distance function is proposed to measure the merits of a satisfactory solution. Finally, a case study for cloud computing pricing problems and several numerical examples are given to verify the applicability and the effectiveness of the proposed models and methods. (C) 2016 Elsevier Ltd. All rights reserved.
multilevel programming is used to model a decentralized planning problem with multiple decision makers in a hierarchical system. This paper aims at providing an uncertain multilevel programming model that is a type of...
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multilevel programming is used to model a decentralized planning problem with multiple decision makers in a hierarchical system. This paper aims at providing an uncertain multilevel programming model that is a type of multilevel programming involving uncertain variables. Besides, a genetic algorithm is employed to solve the model. As an illustration, the uncertain multilevel programming model is applied to a product control problem. (C) 2014 Elsevier Ltd. All rights reserved.
For modeling decentralized decision-making problems with uncertain random parameters, an uncertain random multilevel programming is proposed. For some special case, an equivalent crisp mathematical programming to the ...
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For modeling decentralized decision-making problems with uncertain random parameters, an uncertain random multilevel programming is proposed. For some special case, an equivalent crisp mathematical programming to the established uncertain random programming is presented. A searching method by integrating uncertain random simulations, neural network, and genetic algorithm is produced to search the quasi-optimal solution under some decision-making criterion. Finally, the proposed uncertain random multilevel programming is applied to a production control problem.
In supply chain management, the selection of suppliers is vital and plays a valuable role in the performance of organizations. A hierarchical structure, with different levels in the selection of suppliers, is employed...
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In supply chain management, the selection of suppliers is vital and plays a valuable role in the performance of organizations. A hierarchical structure, with different levels in the selection of suppliers, is employed, wherein sequential decisions are made from the highest to the lowest level. Decision variables, called controlling factors, are divided into several categories. In the decision-making process, often because of the lack of confidence or uncertainty, It becomes challenging for decision-makers to give explicit/crisp values to any parameter, resulting in uncertainty in the problem. In this paper, we address a multi-level supplier selection problem with fuzzy supply and demand. To avoid decision conflicts, superior or upper-level decision-makers give tolerances that could be used as a possible relaxation. Thus, the problem is employed with fuzzy constraints. Based on a neutrosophic decision set, the neutrosophic compromise programming approach (NCPA) is used as a solution technique with the idea of an indeterminacy degree as well as different objectives for membership and non-membership degrees. Membership functions (Linear-type) are used to develop satisfactory solutions by fuzzily describing objective functions and controlling factors. A numerical illustration is provided to demonstrate the validity and appropriateness of NCPA.
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