The multi-focus image fusion method is used in image processing to generate all-focus images that have large depth of field (DOF) based on original multi-focus images. Different approaches have been used in the spatial and transform domain to fuse multi-focus images. As one of the most popular image processing methods, dictionary-learning-based spare representation achieves great performance in...

So far, many types of location models have been developed to find optimal spatial patterns according to different spatial metrics such as cost, coverage and availability.  The initial focus of these models is on the location availability of service providers and demand estimates, and some of these models are within the framework of multi-objective programming models.  After the advent of scienc...

Probabilistic or stochastic programming is a framework for modeling optimization problems that involve uncertainty.In this paper, we focus on multi-objective linear programmingproblems in which the coefficients of constraints and the righthand side vector are fuzzy random variables. There are several methodsin the literature that convert this problem to a stochastic or<b...

In this paper, we focus on the Data Envelopment Analysis (DEA)-based model structures have been used in assessing bank branch efficiency. Probing the methodologies of 75 published studies at the branch level since 1985 to early 2015, we found that these models can be divided into four categories: standard basic DEA models, single level and multi-level models, enriched (hybrid) models and specia...

In recent years, the issue of energy consumption modeling techniques in the building sector has been widely considered by researchers and managers. Researches indicate that energy consumption in residential sector is one of the main parts of the total consumption. Moreover, the urban residence is supposed as a significant consumer of energy in every country and therefore a focus for energy cons...

Numerical simulations have recently shown their potential as a robust, cheap and reliable tool for predicting the quality of components produced by metal additive manufacturing (MAM) processes. Despite advantages MAM processes over conventional methods, there is still lack thorough understanding on how different defects can form originate during processing. In that respect, advanced numerical t...