A bi-level programming model for oilfield development and its solution algorithm based on interactive intuitionistic fuzzy method

The theory of interval-valued intuitionistic fuzzy sets provides an intuitive and feasible way of addressing uncertain and ambiguous properties. Many useful models and methods have been developed for multiple criteria decision analysis within the interval-valued intuitionistic fuzzy environment. In contrast to the elaborate existing methods, this paper establishes a simple and effective method for managing the sophisticated data expressed by interval-valued intuitionistic fuzzy sets. An inclusion comparison possibility defined on interval-valued intuitionistic fuzzy sets is proposed, and some important properties are investigated. Then, an inclusion-based index that considers positive and negative ideals is offered. Considering the maximal comprehensive inclusion-based indices, this paper constructs a linear programming model (for consistent information) and an integrated, nonlinear programming model (for inconsistent information) to estimate the criterion weights and the optimal ranking order of the alternatives under an incomplete preference structure. The feasibility of the proposed method is illustrated by a practical example of selecting a suitable bridge construction method, and a comparative analysis with other relevant methods is conducted to validate the effectiveness and applicability of the proposed methodology.

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A Multi-Level Programming Model and Solution Algorithm for the Location of Distribution Centers with Uncertainty Demand

Dynamics in Logistics - Lecture Notes in Logistics ◽

10.1007/978-3-642-35966-8_27 ◽

2013 ◽

pp. 327-336

Author(s):

Patareeya Lasunon ◽

Raknoi Akararungruangkul

Keyword(s):

Programming Model ◽

Solution Algorithm ◽

Distribution Centers ◽

Multi Level

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A Hybrid Dynamic Programming for Solving Fixed Cost Transportation with Discounted Mechanism

Journal of Optimization ◽

10.1155/2016/8518921 ◽

2016 ◽

Vol 2016 ◽

pp. 1-9

Author(s):

Farhad Ghassemi Tari

Keyword(s):

Dynamic Programming ◽

Programming Model ◽

Transportation Network ◽

Dynamic Programming Algorithm ◽

Optimal Solution ◽

Transportation Cost ◽

Solution Algorithm ◽

Transportation Costs ◽

Programming Algorithm ◽

Fixed Cost

The problem of allocating different types of vehicles for transporting a set of products from a manufacturer to its depots/cross docks, in an existing transportation network, to minimize the total transportation costs, is considered. The distribution network involves a heterogeneous fleet of vehicles, with a variable transportation cost and a fixed cost in which a discount mechanism is applied on the fixed part of the transportation costs. It is assumed that the number of available vehicles is limited for some types. A mathematical programming model in the form of the discrete nonlinear optimization model is proposed. A hybrid dynamic programming algorithm is developed for finding the optimal solution. To increase the computational efficiency of the solution algorithm, several concepts and routines, such as the imbedded state routine, surrogate constraint concept, and bounding schemes, are incorporated in the dynamic programming algorithm. A real world case problem is selected and solved by the proposed solution algorithm, and the optimal solution is obtained.

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Evaluation research on commercial bank counterparty credit risk management based on new intuitionistic fuzzy method

Soft Computing ◽

10.1007/s00500-018-3042-z ◽

2018 ◽

Vol 22 (16) ◽

pp. 5363-5375 ◽

Cited By ~ 1

Author(s):

Qian Liu ◽

Chong Wu ◽

Lingyan Lou

Keyword(s):

Risk Management ◽

Credit Risk ◽

Commercial Bank ◽

Evaluation Research ◽

Credit Risk Management ◽

Fuzzy Method ◽

Intuitionistic Fuzzy ◽

Counterparty Credit Risk

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Subjective Risk Estimation of the Rare Event

Journal of KONES ◽

10.2478/kones-2019-0013 ◽

2019 ◽

Vol 26 (1) ◽

pp. 103-110

Author(s):

Hoang Nguyen

Keyword(s):

Probabilistic Models ◽

Rare Events ◽

Practical Knowledge ◽

Risk Estimation ◽

Rare Event ◽

Severe Accident ◽

Fuzzy Method ◽

Ship Propulsion ◽

Intuitionistic Fuzzy ◽

Subjective Estimation

Abstract In the safety engineering, the most frequently disadvantage in risk estimation is the lack of data. In such cases, we have to rely on subjective estimations made by persons with practical knowledge in the field of interest, i.e. experts. However, in some realistic situations, they may have uncertainty in the perceiving and evaluation of the problem considered or limited knowledge of the rare events, such as the consequences of the seagoing ship propulsion failures. The probabilistic models of the risk estimation turn out to be insufficient in modelling the subjective uncertainty. The fuzzy methods are viewed to be powerful in dealing with ambiguity and uncertainty that can be used to handle with the subjective estimation. This article addresses the intuitionistic fuzzy method in the subjective estimation of the ship propulsion failure consequences as rare event risk. In the article, a subjective model of the ship propulsion risk is developed as scenarios of the different subsequent consequences of loss of ship propulsion function until a seriously severe accident resulting in loss of seaworthiness. The model proposes an approach combining AHP method and intuitionistic fuzzy method to assess the occurrence probability and severe probability of these rare events based on the expert opinions. In order to show the applicability of the proposed model, a study case of the propulsion risk of the container carrier operating on the North Atlantic lines is conducted.

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Effectiveness Evaluation Method of Constellation Satellite Communication System with Acceptable Consistency and Consensus Under Probability Hesitant Intuitionistic Fuzzy Preference Relationship

10.21203/rs.3.rs-1016226/v1 ◽

2022 ◽

Author(s):

Yanjun Wang ◽

Xiaoxuan Hu ◽

Lidong Wang

Keyword(s):

Communication System ◽

Satellite Communication ◽

Evaluation Method ◽

Programming Model ◽

Consistency Index ◽

Effectiveness Evaluation ◽

Satellite Communication System ◽

Intuitionistic Fuzzy ◽

Priority Weights ◽

Fuzzy Preference

Abstract System effectiveness evaluation is an important part of constellation satellite communication system research, with applications in project verification and optimization as well as tactical and technical measurement argumentation. This paper presents a systematic and comprehensive effectiveness evaluation method for a constellation satellite communication system under a probabilistic hesitant intuitionistic fuzzy preference relationship (PHIFPR), aiming to better address the fuzziness and uncertainty in effectiveness evaluation. First, a proposed definition of PHIFPR describes the hesitancy of evaluators, provides hesitancy distribution information, and depicts the worst negative information and risk preferences in effectiveness evaluation. Then, we deduce the approximate consistency index of PHIFPR and establish a mathematical programming model to increase individual consistency when the approximate consistency index does not reach a predetermined level. In the sequel, a proposed group consensus index uses the PHIFPR-based Hausdorff distance to measure the closeness between evaluators' judgements. Afterwards, a consistency and consensus improvement model is designed to retain the original opinions of evaluators to make the consistency and consensus of PHIFPRs acceptable. Moreover, a goal programming model is established to gain the reliable scheme priority weights by regarding the approximate consistency condition of a PHIFPR as a fuzzy constraint. Finally, an experimental example is offered to highlight the practicability and feasibility of the proposed method, and some comparative analyses with other methods offer insights into the designed method.

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