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Communication networks are prone to failures due to targeted attacks or large-scale disasters. Networks can be improved to withstand challenges using mechanisms such as diversity, which can simply be improved by adding links, however achieving maximum resilience is not feasible due to limited budget. Therefore, algorithms that improve the diversity of networks cost-efficiently are necessary. In this...
The optimization of power transformers is one of the earliest applications of geometric programming. This approach works well with shell-form transformers, and the constructed models can be solved accurately with the new interior point method based solvers. However, a less well-known fact is that this kind of modeling becomes problematic in the case of core-form transformers. This paper shows a new...
In population-based optimization algorithms (POAs) such as particle swarm optimization (PSO), if landscape modality of an objective function can be identified, strategies of the POAs can be selected properly. We have proposed a method that estimates the landscape modality by sampling some points along a line and counting the number of changes in the objective values from increasing to decreasing and...
In artificial intelligence field, dynamic optimization problem under uncertain environment has always been a main topic and been widely researched these years. How to find the optimal solution around the goals to be solved is the key problem. As a typical case of uncertainty environment, maze has an important research value. In this paper we design a complex maze of random scene simulation system...
Particle swarm optimization algorithm is a simple and effective modern optimization algorithm, but it has the problem of being prone to premature and its convergence rate is slow. A new improved PSO algorithm is hence proposed. In the iteration of the proposed algorithm, the particles are distinguished to be active or stable according to their velocity information. For the active particles, to maintain...
The quadratic assignment problem (QAP) is a classic combinatorial optimization problem, which is of the NP-hard nature. In this paper, a hybrid artificial fish school optimization algorithm (HAFSOA) is proposed. In HAFSOA, the heuristic information is used in constructing some better initial individuals and its search ability of the global optimal solution is improved by a combination of the modified...
Classical binary or 0-1 knapsack problem is one of the most widely studied problems in combinatorial optimization. Though the optimization version of this problem is NP-hard, practical solution techniques don't require optimality. Many different heuristics and approximation algorithms have been used to solve t it. Cellular competitive decision algorithm (CCDA) is a heuristic proposed recently, which...
Among all combinatorial optimization problems, traveling salesman problem (TSP) is one of the widely studied problems. Though the optimization version of this problem is NP-hard, practical solution techniques don't require optimality. And many different heuristics and approximation algorithms are used to solve this problem. Cellular competitive decision algorithm (CCDA) is a new heuristic for solving...
Software-as-a-Service (SaaS) is a delivery model whose basic idea is to provide applications to the customer on demand over the Internet. Thereby, SaaS promotes multi-tenancy as a tool to exploit economies of scale. A major drawback of SaaS is the customers' hesitation of sharing infrastructure, application code, or data with other tenants. The common way in research to address this problem is to...
Our aim is to develop a bacterial-based swarm algorithm that adjusts the parameter values of a fuzzy model. The bacterial-based swarm algorithm is simplified in order to adjust the parameters of the fuzzy model. The procedure of the bacterial swarm algorithm simulates the movement of an E. coli bacterium through swimming and tumbling in problem search space in order to find the optimal solution. A...
The problem of realization of optimization algorithm for charged particle dynamics in an axially symmetric electric field is considered. The complex potential is represented as a Cauchy integral of a function defined on the boundary of the region and considered as the control function. The Cosy Infinity software package is used for the algorithm implementation.
Although the university course timetabling problem (UCTP) is an old, classical problem in the field of optimization problems, there are still a few challenges for the practical-relevant problems considering customers' requirements. In particular with respect to the UCTP of China, the timetable planning based on the uniform teaching resources of a university for all degree types of undergraduates and...
Metaheuristic optimization algorithms have become popular choice for solving complex and intricate problems which are difficult to solve by traditional methods. Particle swarm optimization has shown an effective performance for solving variant benchmark and real-world optimization problems. However, it suffers from premature convergence because of quick losing of diversity. In order to enhance its...
The generalized predictive control is applied to the industrial arc furnace electrode regulator system. The detailed design procedure of the generalized predictive controller is presented. Based on multi-step prediction, rolling optimization and online correction, the optimal control law is obtained. The results of simulation show that this proposed algorithm can restrain arc disturbance effectively,...
With the development of intelligent algorithm, GA and PSO have become the hot spot for the study on multi-objective optimization in recently years. Information sharing is the core of PSO algorithm, Comparing with GA, PSO algorithm has less variables to adjust and is easy to achieve, so it is widely used in engineering. This paper focus on the comparation on several PSO algorithm and introduce a kind...
For the system with both polytopic uncertainty and bounded disturbance, an off-line approach to the dynamic output feedback robust model predictive control is considered. To reduce the on-line computational burden, a look-up table is constructed off-line for on-line searching the real-time control parameters. During the on-line searching stage, if an off-line calculated ellipsoidal region of attraction...
An improved harmony search algorithm is presented for solving continuous optimization problems in this paper. In the proposed algorithm, an elimination principle is developed for choosing from the harmony memory, so that the harmonies with better fitness will have more opportunities to be selected in generating new harmonies. Two key control parameters, pitch adjustment rate (PAR) and bandwidth distance...
We present a memory-efficient algorithm and its implementation for solving multidimensional numerical integration on a cluster of compute nodes with multiple GPU devices per node. The effective use of shared memory is important for improving the performance on GPUs, because of the bandwidth limitation of the global memory. The best known sequential algorithm for multidimensional numerical integration...
Aiming at optimizing Web service composition which satisfies user's multiple QoS constraints, an efficient graph-based Web service composition approach, named Skyline improved Multi Constraint Shortest Path-Relax (Sky-MCSP-R), is proposed. Firstly, the approach selects Skyline services from candidate service spaces, thus it can construct the model of Web service composition directly on these high...
Inspired by the concept and principles of quantum computing, the classical quantum-inspired evolutionary algorithm (QEA) provides a useful way to find out the approximate solution of many optimization problems. However, compared with other heuristic algorithms, the slow convergence speed of QEA has been an important issue when it is applied to solve the optimization problems. As such, an improved...
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