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The Islamic financial system consists of three functional areas of Islamic banking, Islamic insurance and the Islamic capital market, which, with its development and progress, has become an important part of the global financial market and as an alternative, efficient financial model in front of the financial system. Takaful insurance is a relatively new but growing sector of the Islamic financial industry. Today, this insurance has attracted the attention of many researchers and executives. To further improve, it is important to identify the key factors according to the demand and also to evaluate their importance. In Iran’s insurance industry, Takaful product has not yet been released, and insurers have recently entered this field. Therefore, the purpose of this paper, an attempt has been made to identify the factors affecting the demand for Takaful insurance in Iran. The results of this research can be useful for policymakers and Takaful providers in formulating appropriate strategies to increase the demand for Takaful insurance.

In this regard, in this research, using library studies, indicators affecting demand were identified. After that, using a field study and distributing a questionnaire among experts in the field of research, the importance of the indicators was analyzed relative to each other and the indicators were ranked based on their importance.

Based on the results, the indicators are divided into five categories of economic, social, demographic, marketing and sales and features of Takaful insurance products.

To the best of the authors’ knowledge, this is the first study regarding the identification and ranking of factors affecting the demand for Takaful insurance in Iran’s insurance industry.

In recent decades, development of effective methods for optimizing a set of conflicted objective functions has been absorbing an increasing interest from researchers. This refers to the essence of real-life engineering systems and complex natural mechanisms which are generally multi-modal, non-convex and multi-criterion. Until now, several deterministic and stochastic methods have been proposed to cope with such complex systems. Advanced soft computational methods such as evolutionary games (cooperative and non-cooperative), Pareto-based techniques, fuzzy evolutionary methods, cooperative bio-inspired algorithms and neuro-evolutionary systems have effectively come to the aid of researchers to build up efficient paradigms with application to vector optimization. The paper aims to discuss this issue.

A novel hybrid algorithm called synchronous self-learning Pareto strategy (SSLPS) is presented for the sake of vector optimization. The method is the ensemble of evolutionary algorithms (EA), swarm intelligence (SI), adaptive version of self-organizing map (CSOM) and a data shuffling mechanism. EA are powerful numerical optimization algorithms capable of finding a global extreme point over a wide exploration domain. SI techniques (the swarm of bees in our case) can improve both intensification and robustness of exploration. CSOM network is an unsupervised learning methodology which learns the characteristics of non-dominated solutions and, thus, enhances the quality of the Pareto front.

To prove the effectiveness of the proposed method, the authors engage a set of well-known benchmark functions and some well-known rival optimization methods. Additionally, SSLPS is employed for optimal design of shape memory alloy actuator as a nonlinear multi-modal real-world engineering problem. The experiments show the acceptable potential of SSLPS for handling both numerical and engineering multi-objective problems.

To the author’s best knowledge, the proposed algorithm is among the rare multi-objective methods which fosters the use of automated unsupervised learning for increasing the intensity of Pareto front (while preserving the diversity). Also, the research evaluates the power of hybridization of SI and EA for efficient search.

A computational fluid dynamics (CFD) analysis has been carried out on the aerodynamic and thermal behavior of an incompressible Newtonian fluid having a constant property and flowing turbulently through a two-dimensional horizontal high-performance heat transfer channel with a rectangular cross section. The top surface of the channel was kept at a constant temperature, while it was made sure to maintain the adiabatic condition of the bottom surface. Two obstacles, with different shapes, i.e. flat rectangular and V-shaped, were inserted into the channel; they were fixed to the top and bottom surfaces of the channel in a periodically staggered manner to force vortices to improve the mixing and consequently the heat transfer. The first fin-type obstacle is placed on the heated top channel surface, and the second baffle-type one is placed on the insulated bottom surface. Five different obstacle situations were considered in this study, which are referred as cases FF (flat fin and flat baffle), FVD (flat fin and V-downstream baffle), FVU (flat fin and V-upstream baffle), VVD (V-downstream fin and V-downstream baffle) and VVU (V-Upstream fin and V-upstream baffle).

The flow model is governed by Reynolds-averaged Navier–Stokes equations with the k-epsilon turbulence model and the energy equation. These governing equations are discretized by the finite volume method, in two dimensions, using the commercial CFD software FLUENT software with the Semi Implicit Method for Pressure Linked Equations (SIMPLE) algorithm for handling the pressure-velocity coupling. Air is the test fluid with the flow rate in terms of Reynolds numbers ranging from 12,000 to 32,000.

Important deformations and large recirculation regions were observed in the flow field. A vortex causes a rotary motion inside the flow field, which enhances the mixing by bringing the packets of fluid from the near-wall region of the channel to the bulk and the other way around. The largest value of the axial variations of the Nusselt number and skin friction coefficient is found in the region facing the baffle, while the smallest value is in the region near the fin, for all cases. The thermal enhancement factor (TEF) was also introduced and discussed to assess the performance of the channel for various obstacle situations. It is found that the TEF values are 1.273-1.368, 1.377-1.573, 1.444-1.833, 1.398-1.565 and 1.348-1.592 for FF, FVD, FVU, VVD and VVU respectively, depending on the Re values. In all cases, the TEF was found to be much larger than unity; its maximum value was around 1.833 for FVU at the highest Reynolds number. Therefore, the FVU may be considered as the best geometrical configuration when using the obstacles to improve the heat transfer efficiency inside the channel.

This study can be a real application in the field of shell-and-tube heat exchangers and flat plate solar air collectors.