Numerical Solution of Second-Orders Fuzzy Linear Differential Equation

In this paper, the numerical solution of the boundary value problem that is two-order fuzzy linear differential equations is discussed. Based on the generalized Hukuhara difference, the fuzzy differential equation is converted into a fuzzy difference equation by means of decentralization. The numerical solution of the boundary value problem is obtained by calculating the fuzzy differential equation. Finally, an example is given to verify the effectiveness of the proposed method.

Fuzzy TOPSIS method to primary crusher selection for Golegohar Iron Mine(Iran)

Selection of the crusher required a great deal of design regarding to the mine planning. Selection of suitable primary crusher from all of available primary crushers is a multi-criterion decision making(MCDM) problem. The present work explores the use of technique for order performance by similarity to ideal solution(TOPSIS) with fuzzy set theory to select best primary crusher for Golegohar Iron Mine in Iran. Gyratory, double toggle jaw, single toggle jaw, high speed roll crusher, low speed sizer, impact crusher, hammer mill and feeder breaker crushers have been considered as alternatives. Also, the capacity, feed size, product size, rock compressive strength, abrasion index and application of primary crusher for mobile plants were considered as criteria for solution of this MCDM problem. To determine the order of the alternatives, closeness coefficient is defined by calculating the distances to the fuzzy positive ideal solution(FPIS) and fuzzy negative ideal solution(FNIS). Results of our work based on fuzzy TOPSIS method show that the gyratory is the best primary crusher for the studied mine.

Optimization Model on Quadratic Programming Problem with Fuzzy

In this paper, the authors propose a computational procedure by using fuzzy approach to fred the optimal solution of quadratic programming problems. The authors divide the calculation of the optimal solution into two stages. In the first stage the authors determine the unconstrained minimization and check its feasibility. The second stage, the authors explore the feasible region from initial point to another point until the authors get the optimal point by using Lagrange multiplier. A numerical example is included to support as illustration of the paper.

FUZZY SATISFYING INTERACTIVE MULTIOBJECTIVE THERMAL POWER DISPATCH： SWT APPROACH

In multiobjective optimization, trade-off analysis plays an important role in determining most preferred solution. This paper presents an explicit interactive trade-off analysis based on the surrogate worth trade-off function to determine the best compromised solution. In the multiobjective framework thermal power dispatch problem is undertaken in which four objectives viz. cost, NOx emission, SOx emission and COx emission are minimized simultaneously. The interactive process is implemented using a weighting method by regulating the relative weights of objectives in systematic manner. Hence the weighting method facilitates to simulate the trade-offrelation between the conflicting objectives in non-inferior domain. Exploiting fuzzy decision making theory to access the indifference band, interaction with the decision maker is obtained via surrogate worth trade-off （SWT） functions of the objectives. The surrogate worth trade-off functions are constructed in the functional space and then transformed into the decision space, so the surrogate worth trade-off functions of objectives relate the decision maker＇s preferences to non-inferior solutions through optimal weight patterns. The optimal solution of thermal power dispatch problem is obtained by considering real and reactive power losses. Decoupled load flow analysis is performed to find the transmission losses. The validity of the proposed method is demonstrated on 11-bus, 17-lines IEEE system, comprising of three generators.

Analysis of Supply Chain Sustainability Drivers in the Oil and Gas Industry under Covid-19 Pandemic

The supply chain of many industries,including Oil and Gas,was significantly affected by the disruption caused by the Covid pandemic.This,in turn,had a knock-on effect on other industries around the globe.Sustaining the impact of the disruption posed a major challenge for the industry.This study contributes to the existing literature by identifying and analyzing the most significant drivers that affected the sustainability of the Oil and Gas supply chain during the Covid pandemic.Fifteen drivers were identified based on an extensive literature review and a survey conducted with experts working in the Oil and Gas industry.Multi-criteria decision-making methodologies were used to analyze these drivers.The analysis from the fuzzy analytical hierarchy process found that the most important drivers for the sustainability of the Oil and gas supply chain during the pandemic were"Risk management capacity","Government regulation"and"Health and safety of employees".On the other hand,the driver"Community Pressure"was found to be of the least importance.Furthermore,the study integrated the results of the fuzzy analytical hierarchy process with the fuzzy technique for order of preference by similarity to ideal solution to calculate the supply chain sustainability index.A case example was demonstrated to rank the industries based on such calculations.This study can support the governmental institutions in benchmarking the Oil and Gas industry based on its sustainability index.Additionally,the outcomes of the study will help industrial decision makers prioritize the drivers the company should focus and devise strategies based on the priority to improve the sustainability of their supply chain during severe disruption.This will be crucial as the World health organization has cautioned that the world may encounter another pandemic in the near future.