Investment decision making is one of the key issues in financial management. Selecting the appropriate tools and techniques that can make optimal portfolio is one of the main objectives of the investment world. This study tries to optimize the decision making in stock selection or the optimization of the portfolio by means of the artificial colony of honey bee algorithm. To determine the effect...

Hyper-heuristics are (meta-)heuristics that operate at a high level to choose or generate a set of low-level (meta-)heuristics to solve difficult search and optimisation problems. Evolutionary algorithms are well-known natureinspired meta-heuristics that simulate Darwinian evolution. In this article, we introduce an evolutionary-based hyper-heuristic in which a set of low-level heuristics compe...

the markowitz’s optimization problem is considered as a standard quadratic programming problem that has exact mathematical solutions. considering real world limits and conditions, the portfolio optimization problem is a mixed quadratic and integer programming problem for which efficient algorithms do not exist. therefore, the use of meta-heuristic methods such as neural networks and evolutionar...

The problem of searching for the best values ​​of fuzzy logic parameters (T1FLS) is consider complex problems, and type-2 system (T2FLS) more complex, in special case interval (IT2FLS). Researchers have used many methods algorithms to solve this problem, among most important field are the)Meta-heuristic) algorithms. Because Meta-heuristic a high capacity practical field, so we one modern which ...

Algorithmic – based search approach is ineffective at addressing the problem of multi-dimensional feature selection for document categorization. This study proposes use meta heuristic optimal selection. Elephant optimization (EO) and Ant Colony (ACO) algorithms coupled with Naïve Bayes (NB), Support Vector Machin (SVM), J48 classifiers were used to highlight capability meta-heuristic in In addi...

The human has always been to find the best in all things. This Perfectionism has led to the creation of optimization methods. The goal of optimization is to determine the variables and find the best acceptable answer Due to the limitations of the problem, So that the objective function is minimum or maximum. One of the ways inaccurate optimization is meta-heuristics so that Inspired by nature, ...

This paper presents application of an improved Harmony Search (HS) technique and Charged System Search algorithm (CSS) to estimate transport energy demand in Iran, based on socio-economic indicators. The models are developed in two forms (exponential and linear) and applied to forecast transport energy demand in Iran. These models are developed to estimate the future energy demands based on pop...

This paper presents a novel population-based meta-heuristic algorithm inspired by the game of tug of war. Utilizing a sport metaphor the algorithm, denoted as Tug of War Optimization (TWO), considers each candidate solution as a team participating in a series of rope pulling competitions.  The  teams  exert  pulling  forces  on  each  other...

In this paper an effort is made to present a state-of-the-art review of meta-heuristic approaches in solving facility layout problems. Facility layout directly affects the productivity of the industries so it is very important to solve it carefully. There are many approaches, methods and techniques to solve and optimize the layout problem. The current and future trends involving design objectiv...