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The problem of converting floating point algorithms to implementation friendly fixed point formats is often solved as an optimization problem where the precision is traded to gain in the implementation cost. The complexity of the problem is known to grow exponentially with more optimizable variables. This paper proposes a divide and conquer technique to solve the growing size of the problem. The approach...
D-optimality is adopted in the optimum design of accelerated life testing in recent years. However, for some cases, the optimization results tend to approach the extreme stress levels and processing accelerated life testing under such stress levels would not obtain much information about lifetime and reliability of the test units. This paper presents an optimum design of constant stress accelerated...
In a retrieval system for vast amounts of image data, the primary storage cannot hold all image feature vectors because a huge data capacity would be required. Therefore, it is necessary to handle a slow-access secondary storage effectively as well as a first-access primary storage. In this paper, we propose a data-alignment optimization method in the secondary storage to access fast. Our idea is...
Differential Evolution (DE) is generally considered as a reliable, accurate and robust optimization technique. However, the algorithm suffers from slow convergence rate and takes large computational time for optimizing the computationally expensive objective functions. Therefore, an attempt to speed up DE is considered necessary. This research introduces a modified differential evolution, called Ant...
In the present study a Modified Differential Evolution (MDE) algorithm is proposed. This algorithm is different in three ways from basic DE. For initialization it utilizes opposition-based learning while in basic DE uniform random numbers serve this task. Secondly, in basic DE mutant individual is random while in MDE it is tournament best and finally MDE utilizes only one set of population as against...
Mixed-model assembly lines typically rely in intermediate stock buffers to handle disturbances and optimize the car sequence between the main workshops in the plant. The optimization of these buffers is often constrained by installation and production specific rules. In this paper an algorithm for the stock management of buffers with drawers is proposed to handle constraints induced by the production's...
This paper considers the optimal traffic signal setting for an urban arterial road. The traffic lights are configured to minimize the average waiting time of vehicles through the way. By introducing the concept of non-synchronism degree, a mathematical model is constructed and an optimization problem is posed. Finally, the setting plan is obtained through the solution of the model as given the inputting...
In this paper, we study a no-centralize newsvendor model with re-distributed decision-making power. It is different from classical model that sale process is distinguished normal sale and promotion stages. Vendor own to the right of promotion policy selected to management promotion action for increasing their return when real demand is lacking. We get two mathematical expressions of traditional optimization...
The paper establishes a mathematical model of the blind source separation (BSS),and introduce the basic theory of ant colony optimization (ACO) algorithm. According to the idea of independent component analysis (ICA), the paper proposes a linear blind source separation algorithm based on ant colony optimization, the algorithm establishes a cost function based on minimum mutual information (MMI).The...
Data clustering plays an important role in many disciplines, including data mining, machine learning, bioinformatics, pattern recognition, and other fields. When there is a need to learn the inherent grouping structure of data in an unsupervised manner, ant-based clustering stand out as the most widely used group of swarm-based clustering algorithms. Under this perspective, this paper presents a new...
To satisfy the customer's requirements, the linear optimization model is established. Using the Matlab as the optimized tool, the optimized solutions are obtained. A universal normalization method is chosen to normalize the binary vectors. The Technique for Order Preference by Similarity to Ideal Solution method is applied to configuration field to get ??ideal product?? of the ideal solution. The...
In this paper we propose a fractional PIα-PDβ controller that tuned with integral performance criterion. The orders of the integral and derivative parts, α and β, respectively, are fractional. This controller is a generalization of a conventional PI-PD controller. This expansion could provide much more flexibility than a conventional PI-PD controller design. The tuning method is based on the solution...
This paper investigates the cluster problems of which both the characteristic values and weights of indices are triangular fuzzy numbers. A new maximal tree clustering analysis method is proposed. First, several operational laws of two triangular fuzzy numbers are given. Next, the similarity coefficient is generalized to the triangular fuzzy numbers. Then an clustering algorithm for multiple attribute...
In this paper, we will propose two types of tolerant fuzzy c-means clustering with regularization terms. One is L2-regularization term and the other is L1-regularization one for tolerance vector. Introducing a concept of clusterwise tolerance, we have proposed tolerant fuzzy c-means clustering from the viewpoint of handling data more flexibly. In tolerant fuzzy c-means clustering, a constraint for...
Various applications, such as mesh composition and model repair, ask for a natural stitching for polygonal surfaces. Unlike the existing algorithms, we make full use of the information from the two feature lines to be stitched up, and present an accurate stitching method for polygonal surfaces, which minimizes the error between the feature lines. Given two directional polylines as the feature lines...
In this paper, a new fuzzy optimization based methodology called as a modified S-curve membership function has been utilized in an industrial production problems of oil company. The major contribution of this paper is on the optimization of profit function with respect to uncertain resource variables and technological coefficients. Three cases have been thoroughly studied in this paper. Comparative...
Supply chain selection and sale price decision problem in one product family can be formulated as a profit-driven optimization problem in which the decision variables are supplier options, retail sale prices, and whole sale prices for all product variants and the object is to maximize the profit of the decision-making leader. Two supply chain options are considered under stochastic and price-dependent...
This paper presents a cross-layer approach for optimizing the delay performance of a multiuser diversity system with heterogeneous block-fading channels and a delay-sensitive bursty-traffic. We consider the downlink of a time-slotted multiuser system employing opportunistic scheduling with fair performance at the medium access (MAC) layer and adaptive modulation and coding (AMC) with power control...
This paper proposes an algorithm for planning Cinfin paths with bound curvature and curvature derivative linking two fixed (initial and final) configurations and passing through a given number of intermediate via-points. The proposed solution is derived solving an optimization problem such that a smooth curve of bounded curvature and curvature derivative approximates Dubin's shortest paths. The effectiveness...
This paper investigates the problem of state estimation for nonlinear discrete-time dynamic systems. The estimator is parameterized as a linear combination of chosen basis functions. We seek the parameter that minimizes the mean squared estimation error (MSE); however, computing this objective is intractable. Hence, the MSE is approximated using the scaled unscented transform (SUT), which yields a...
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