نتایج جستجو برای: nsga optimization
تعداد نتایج: 318922 فیلتر نتایج به سال:
In today’s computer architectures the design spaces are huge, thus making it very difficult to find optimal configurations. One way to cope with this problem is to use Automatic Design Space Exploration (ADSE) techniques. We developed the Framework for Automatic Design Space Exploration (FADSE) which is focused on microarchitectural optimizations. This framework includes several state-of-the ar...
The growing importance of electric distribution systems justifies new investments in their expansion and evolution. It is well known in the literature that optimization techniques can provide better allocation of the financial resources available for such a task, reducing total installation costs and power losses. In this work, the NSGA-II algorithm is used for obtaining a set of efficient solu...
Non-dominated Sorting Genetic Algorithm (NSGA) has established itself as a benchmark algorithm for Multi objective Optimization. The determination of pareto-optimal solutions is the key to its success. However the basic algorithm for big problem gives less efficient results, which renders it less useful for practical applications. Among the variants of NSGA, several attempts have been made to r...
The gaining returns in line with risks is always a major concern for market play-ers. This study compared the selection of stock portfolios based on the strategy of buying and retaining winning stocks and the purchase strategy based on the level of investment risks. In this study, the two-step optimization algorithms NSGA-II and SPEA-II were used to optimize the stock portfolios. In order to de...
Bi-objective portfolio optimization for minimizing risk and maximizing expected return has received considerable attention using evolutionary algorithms. Although the problem is a quadratic programming (QP) problem, the practicalities of investment often make the decision variables discontinuous and introduce other complexities. In such circumstances, usual QP solution methodologies can not alw...
Word alignment is a key task in statistical machine translation (SMT). This paper presents a novel model for this task. In this model, word alignment is considered as amultiobjective optimization problem and solved based on the non-dominated sorting genetic algorithm II (NSGA-II), which is one of the best multiobjective evolutionary algorithms (MOEA). There are two advantages of the proposed mo...
In recent years, web services technology is becoming increasingly popular because of the convenience, low cost and capacity to be composed into high-level business processes. The service location-allocation problem for a web service provider is critical and urgent, because some factors such as network latency can make serious effect on the quality of service (QoS). This paper presents a multi-o...
This paper describes a scalable algorithm for solving multiobjective decomposable problems by combining the hierarchical Bayesian optimization algorithm (hBOA) with the nondominated sorting genetic algorithm (NSGA-II) and clustering in the objective space. It is first argued that for good scalability, clustering or some other form of niching in the objective space is necessary and the size of e...
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