On the performance of a hybrid genetic algorithm in dynamic environments

The ability to track the optimum of dynamic environments is important in many practical applications. In this paper, the capability of a hybrid genetic algorithm (HGA) to track the optimum in some dynamic environments is investigated for different functional dimensions, update frequencies, and displacement strengths in different types of dynamic environments. Experimental results are reported by using the HGA and some other existing evolutionary algorithms in the literature. The results show that the HGA has better capability to track the dynamic optimum than some other existing algorithms.Comment: This paper has been submitted to Applied Mathematics and Computation on May 22, 2012 Revised version has been submitted to Applied Mathematics and Computation on March 1, 201

A Weight-coded Evolutionary Algorithm for the Multidimensional Knapsack Problem

A revised weight-coded evolutionary algorithm (RWCEA) is proposed for solving multidimensional knapsack problems. This RWCEA uses a new decoding method and incorporates a heuristic method in initialization. Computational results show that the RWCEA performs better than a weight-coded evolutionary algorithm proposed by Raidl (1999) and to some existing benchmarks, it can yield better results than the ones reported in the OR-library.Comment: Submitted to Applied Mathematics and Computation on April 8, 201

Data Center Based on Cloud Computing Technology

With the rapid development of Internet applications, the impact on the development of data centers is huge. Domestic data centers attach great importance to the acceptance of cloud computing technology and the construction of application systems. Nowadays, data centers can be effectively transformed into cloud computing development. The operating support environment has become the main consideration and focus of today’s data center development. Under the concept of cloud computing, this article analyzes and builds a new data center that is more in line with the needs of resource management and information construction. Taking the development of data centers based on cloud computing technology as the research object, building data centers through cloud computing technology realizes the acquisition and organization of data and makes full use of resources. A new information resource management system with functions such as classification and query of data, overall processing and analysis of data, backup of data, information management and services has been realized. Before using the cloud computing model, the network deployed a total of 40 virtual servers, and the average CPU utilization rate was less than 40%. Since the establishment of the data center model in this article, the utilization rate of the processor has stabilized at around 95%. Therefore, the data center proposed in this paper greatly improves the utilization of data and speeds up the overall construction of the data center