درخت حوزه‌های تخصصی

Water is a basic demand of sustainable development in most regions of the world. The non-uniform temporal and spatial distribution of water resources will lead to water shortage in arid and semi-arid areas. Pishin catchment is one of the most important catchments in South-East Iran. The basin had been faced with consecutive droughts in recent years. On the other hand, water resources development projects anticipated and necessary in this catchment. Hence, the need for a study to prioritize different scenarios and their effects on the catchment should be considered to overcome these dry periods. The main objective of the present study is to predict water development projects in the study area. Due to the multiplicity of projects and high cost of them, the concurrent execution priority implementation of these projects is considered as an important factor. Fuzzy multiple attribute decision making is a suitable method for comparison, selection and prioritization of the different options taking into account different criteria. Hence, in this study, the effects of the water development projects are predicted using Water Evaluation and Planning System (WEAP) model. The projects according to the economic criteria are evaluated and prioritized with Fuzzy TOPSIS. Six water development projects and criteria including five economic indexes are considered. Based on the results, according to the investigated indicators, increasing irrigation efficiency in agricultural sector and reducing evaporation from the reservoir scenarios have top priority.

Selecting approaches with appropriate accuracy and suitable speed for the purpose of making decision is one of the managers’ challenges. Also investing decision is one of the main decisions of managers and it can be referred to securities transaction in financial markets which is one of the investments approaches. When some assets and barriers of real world have been considered, optimization of stock basket can’t be solved easily, therefore, Meta-Heuristic approach is considered. In this regard, the main goal of this paper is to solve stock portfolio constrained optimization problem by using of Firefly Algorithm (FA) and Imperialist Competitive Algorithm (ICA). In order to do so, daily information of 25 accepted stocks in period of 2010-2016, in Tehran stock market have been used. Results show that Firefly Algorithm (FA) and Imperialist Competitive Algorithm (ICA) showed successful function in constrained optimization of stock portfolio and has acceptable accuracy in finding optimal answers in whole risk and returns levels. Also, the results of comparison of Cardinality Constrained Mean – Variance (CCMV) and Cardinality Constrained Mean – Semi -Variance (CCMSV) portfolios two using of Firefly Algorithm (FA) and Imperialist Competitive Algorithm (ICA) and considering to the findings of two criteria for assessing accuracy in stock basket optimization simultaneously show that Imperialist Competitive Algorithm (ICA) has high speed and accuracy for solving stock basket optimization and could have desirable interaction with real barriers of market. Moreover, there is high accuracy optimization of Cardinality Constrained Mean – Semi -Variance (CCMSV) compared to Cardinality Constrained Mean – Variance (CCMV).