نتایج جستجو برای: objective particle swarm optimization mopso
تعداد نتایج: 998471 فیلتر نتایج به سال:
In this paper, a novel prediction based mean-variance (PBMV) model has been proposed, as an alternative to the conventional Markowitz mean-variance model, to solve the constrained portfolio optimization problem. In the Markowitz mean-variance model, the expected future return is taken as the mean of the past returns, which is incorrect. In the proposed model, first the expected future returns a...
A novel multi-objective evolutionary algorithm (MOEA) is developed based on Imperialist Competitive Algorithm (ICA), a newly introduced evolutionary algorithm (EA). Fast non-dominated sorting and the Sigma method are employed for ranking the solutions. The algorithm is tested on six well-known test functions each of them incorporate a particular feature that may cause difficulty to MOEAs. The n...
Mathematical programming and artificial intelligence (AI) methods are known as the most effective and applicable procedures to form manufacturing cells in designing a cellular manufacturing system (CMS). In this paper, a bi-objective programming model is presented to consider the cell formation problem that is solved by a proposed multi-objective particle swarm optimization (MOPSO). The model c...
In this paper multi objective optimization problem for partitioning process of VLSI circuit optimization is solved using IPO algorithm. The methodology used in this paper is based upon the dynamic of sliding motion along a frictionless inclined plane. In this work, modules and elements of the circuit are divided into two smaller parts (components) in order to minimize the cutsize and area imbal...
Pareto based Multi-Objective Evolutionary Algorithms face several problems when dealing with a large number of objectives. In this situation, almost all solutions become nondominated and there is no pressure towards the Pareto Front. The use of Particle Swarm Optimization algorithm (PSO) in multi-objective problems grew in recent years. The PSO has been found very efficient in solve Multi-Objec...
Reconfigurable Manufacturing System (RMS) justifies the need of hour by combining the high throughput of dedicated manufacturing system with the flexibility of flexible manufacturing systems. At the heart of RMS lies the Reconfigurable Machine Tools which are capable of performing multiple operations in its existing configurations and can further be reconfigured into more configurations which m...
In this paper, considering multiple interference regions simultaneously, an optimal antenna deployment problem for distributed Multi-Input Multi-Output (MIMO) radar is investigated. The optimal antenna deployment problem is solved by proposing an antenna deployment method based on MultiObjective Particle Swarm Optimization (MOPSO). Firstly, we construct a multi-objective optimization problem fo...
Nowadays, the core of the Particle Swarm Optimization (PSO) algorithm has proved to be reliable. However, faced with multi-objective problems, adaptations are needed. Deeper researches must be conducted on its key steps, such as solution set management and guide selection, in order to improve its efficiency in this context. Indeed, numerous parameters and implementation strategies can impact on...
M. Janga Reddy Department of Civil Engineering, Indian Institute of Technology Bombay, Mumbai 400076, India D. Nagesh Kumar (corresponding author) Department of Civil Engineering, Indian Institute of Science, Bangalore 560012, India E-mail: [email protected] Optimal allocation of water resources for various stakeholders often involves considerable complexity with several conflicting go...
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