In this paper, a hybrid TS-DE algorithm based on Tabu search and differential evolution algorithm is proposed to solve the reliability redundancy optimization problem. A differential evolution algorithm is embedded in Tabu search algorithm. TS is applied for searching solutions space, and DE is used for generating neighborhood solutions. The advantages of both algorithms are considered simultan...

Most of the real-life applications have many constraints and they are considered as constrained optimization problems (COPs). In this paper, we present a new hybrid genetic differential evolution algorithm to solve constrained optimization problems. The proposed algorithm is called hybrid genetic differential evolution algorithm for solving constrained optimization problems (HGDESCOP). The main...

Differential Evolution (DE) is a random search algorithm used for function optimization basing on population evolution. It has been proved effective and efficient through years of studies. Among three evolutionary operations, the mutation scheme is believed to have high relation to convergence and diversity during the evolution process. This paper is going to introduce a modified differential e...

Geometric Differential Evolution (GDE) is a very recently introduced formal generalization of traditional Differential Evolution (DE) that can be used to derive specific GDE for both continuous and combinatorial spaces retaining the same geometric interpretation of the dynamics of the DE search across representations. In this paper, we derive formally a specific GDE for the space of genetic pro...

with the rapid development of the internet, the amount of information and data which are produced, are extremely massive. hence, client will be confused with huge amount of data, and it is difficult to understand which ones are useful. data mining can overcome this problem. while data mining is using on cloud computing, it is reducing time of processing, energy usage and costs. as the speed of ...

In a global economy, an efficient supply chain as a main core competency empowers enterprises to provide products or services at the right time in the right quantity, at a low cost. This paper is to plan a single product, multi-echelon, multi-period closed loop supply chain for high-tech products (which have continuous price decrease). Ultimately, considering components rated to procurement, pr...

Differential Evolution (DE) is a novel evolutionary approach capable of handling non-differentiable, non-linear and multi-modal objective functions. DE has been consistently ranked as one of the best search algorithm for solving global optimization problems in several case studies. This paper presents a simple and modified hybridized Differential Evolution algorithm for solving global optimizat...

Differential Evolution (DE) is a powerful yet simple evolutionary algorithm for optimization of real valued, multi modal functions. DE is generally considered as a reliable, accurate and robust optimization technique. However, the algorithm suffers from premature convergence, slow convergence rate and large computational time for optimizing the computationally expensive objective functions. The...

In this context, a novel structure has been proposed for simple Differential Evolutionary (DE) algorithm to solve optimal recloser placement. For this, an operator is added to DE algorithm to adapt concept of the problem. Other contribution of this work is formulating a novel objective function. The proposed objective function has been formulated to improve four reliability indices which consis...