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  • 1
    Online Resource
    Online Resource
    EDP Sciences ; 2022
    In:  RAIRO - Operations Research Vol. 56, No. 4 ( 2022-07), p. 2999-3015
    In: RAIRO - Operations Research, EDP Sciences, Vol. 56, No. 4 ( 2022-07), p. 2999-3015
    Abstract: Whenever there is a mixture of signals of any type, e.g. sounds, images or any other form of source signals, Blind Source Separation (BSS) is the method utilized to separate these signals from the observations. The separation is done without any prior knowledge about the mixing process nor the source signals. In literature multiple algorithms have been deployed for this particular problem, however most of them depends on Independent Component Analysis (ICA) and its variations assuming the statistical independence of the sources. In this paper, we develop a new algorithm improving the separation quality for both independent and dependent sources. Our algorithm used copulas to accurately model the dependency structure and the Hellinger divergence as a distance measure since it can convergence faster and it is robust against noisy source signals. Many simulations were conducted for various samples of sources to illustrate the superiority of our approach compared to other methods.
    Type of Medium: Online Resource
    ISSN: 0399-0559 , 2804-7303
    RVK:
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2022
    detail.hit.zdb_id: 1468388-X
    SSG: 3,2
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  • 2
    Online Resource
    Online Resource
    Elsevier BV ; 2022
    In:  Applied and Computational Harmonic Analysis Vol. 60 ( 2022-09), p. 426-445
    In: Applied and Computational Harmonic Analysis, Elsevier BV, Vol. 60 ( 2022-09), p. 426-445
    Type of Medium: Online Resource
    ISSN: 1063-5203
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2022
    detail.hit.zdb_id: 1461358-X
    SSG: 11
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  • 3
    Online Resource
    Online Resource
    EDP Sciences ; 2022
    In:  RAIRO - Operations Research Vol. 56, No. 4 ( 2022-07), p. 3047-3069
    In: RAIRO - Operations Research, EDP Sciences, Vol. 56, No. 4 ( 2022-07), p. 3047-3069
    Abstract: The main idea of multi-frame super resolution (SR) algorithms is to recover a single high-resolution image from a sequence of low resolution ones of the same object. The success of the SR approaches is often related to a well registration and restoration steps. Therefore, we propose a new approach based on a partial differential equation (PDE)-constrained optimization fluid image registration and we use a fourth order PDE to treat both the registration and restoration steps that guarantee the success of SR algorithms. Since the registration step is usually a variational ill-posed model, a mathematical study is needed to check the existence of the solution to the regularized problem. Thus, we prove the existence and of the well posed fluid image registration and assure also the existence of the used second order PDE in the restoration step. The results show that the proposed method is competitive with the existing methods.
    Type of Medium: Online Resource
    ISSN: 0399-0559 , 2804-7303
    RVK:
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2022
    detail.hit.zdb_id: 1468388-X
    SSG: 3,2
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  • 4
    In: RAIRO - Operations Research, EDP Sciences, Vol. 57, No. 4 ( 2023-07), p. 1843-1876
    Abstract: Maintenance groups play an essential role in the successful operation of large companies and factories. Additionally, data envelopment analysis (DEA) is known as a valuable tool for monitoring the performance of maintenance groups. Especially, in contrast to the conventional DEA models that impose the convexity assumption into the technology, the free disposal hull (FDH) model provides a method for assessing the efficiency without the assumption of convexity and can be considered a valuable tool for determining one of the observed groups as the benchmark for each maintenance group. Meanwhile, because of the stochastic structure of data with lognormal distribution in the maintenance groups, this paper extends the FDH model in stochastic data with the lognormal distribution. Moreover, the method’s capabilities are confirmed based on some theorems, and a simulation study that illustrated the properties of the developed procedure is also performed. The developed methodology is applied to assess the performance of 21 maintenance groups of AZCO under uncertainty conditions.
    Type of Medium: Online Resource
    ISSN: 0399-0559 , 2804-7303
    RVK:
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2023
    detail.hit.zdb_id: 1468388-X
    SSG: 3,2
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  • 5
    In: RAIRO - Operations Research, EDP Sciences, Vol. 56, No. 5 ( 2022-09), p. 3581-3609
    Abstract: With the expansion of competitive markets, supply chain management has become one of the critical issues facing businesses. One of the advantages of sustainable competition for companies is to make supply chain activities more efficient and effective. This paper aims at an integrated closed-loop supply chain (CLSC) problem which is multi-objective, multi-product, multi-period, and multi-level with limited capacities and uncertain conditions of demand and return products. The proposed supply chain network consists of five levels in the forward flow. There are five centers in the backward flow as well. The purpose of this network is to determine the optimal number and location of facilities required in each period and the optimal amount of the transfer flow of products or raw materials through different transportation modes between facilities. In this proposed model, three objective functions are taken into consideration. The first one minimizes all the costs. The second objective function maximizes the quality of products. The third objective function seeks to minimize the sum of deviations from the ideal score of the principal component of each supplier. The data of this research are taken from Pishro Diesel Company. To solve the proposed problem, several methods and algorithms have been used, including unscaled goal programming, boundary objectives, three single-objective meta-heuristic algorithms (PSO, RDA, and TGA), and multi-objective meta-heuristic algorithm (MOGA-II). As the results show, considering products and returned parts in products, a simultaneous practice of forward and reverse supply chains leads to better product quality, less damage to the environment, and lower costs for customers.
    Type of Medium: Online Resource
    ISSN: 0399-0559 , 2804-7303
    RVK:
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2022
    detail.hit.zdb_id: 1468388-X
    SSG: 3,2
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  • 6
    Online Resource
    Online Resource
    EDP Sciences ; 2023
    In:  RAIRO - Operations Research Vol. 57, No. 5 ( 2023-09), p. 2493-2517
    In: RAIRO - Operations Research, EDP Sciences, Vol. 57, No. 5 ( 2023-09), p. 2493-2517
    Abstract: Two major problems are encountered when using fuzzy SVM: (a) the number of local minima increases exponentially with the number of samples and (b) the quantity of required computer storage, required for a regular quadratic programming solver, increases by an exponential magnitude as the problem size expands. The Kernel-Adatron family of algorithms gaining attention lately which has allowed to handle very large classification and regression problems. However, these methods treat different types of samples (Noise, border, and core) with the same manner, which causes searches in unpromising areas and increases the number of iterations. In this work, we introduce a hybrid method to overcome these shortcoming, namely Optimal Recurrent Neural Network Density Based fuzzy Support Vector Machine (Opt-RNN-DBFSVM). This method consists of four steps: (a) characterization of different samples, (b) elimination of samples with a low probability of being a support vector, (c) construction of an appropriate recurrent neural network based on an original energy function, and (d) solution of the system of differential equations, managing the dynamics of the RNN, using the Euler–Cauchy method involving an optimal time step. Thanks to its recurrent architecture, the RNN remembers the regions explored during the search process. We demonstrated that RNN-FSVM converges to feasible support vectors and Opt-RNN-DBFSVM has a very low time complexity compared to RNN-FSVM with constant time step, and KAs-FSVM. Several experiments were performed on academic data sets. We used several classification performance measures to compare Opt-RNN-DBFSVM to different classification methods and the results obtained show the good performance of the proposed method.
    Type of Medium: Online Resource
    ISSN: 0399-0559 , 2804-7303
    RVK:
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2023
    detail.hit.zdb_id: 1468388-X
    SSG: 3,2
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  • 7
    In: Mathematical Modeling and Computing, Lviv Polytechnic National University, Vol. 8, No. 4 ( 2021), p. 761-769
    Abstract: In this paper, a new Blind Source Separation (BSS) method that handles mixtures of noisy independent/dependent sources is introduced. We achieve that by minimizing a criterion that fuses a separating part, based on Kullback–Leibler divergence for either dependent or independent sources, with a regularization part that employs the bilateral total variation (BTV) for the purpose of denoising the observations. The proposed algorithm utilizes a primal-dual algorithm to remove the noise, while a gradient descent method is implemented to retrieve the signal sources. Our algorithm has shown its effectiveness and efficiency and also surpassed the standard existing BSS algorithms.
    Type of Medium: Online Resource
    ISSN: 2312-9794 , 2415-3788
    URL: Issue
    Language: Unknown
    Publisher: Lviv Polytechnic National University
    Publication Date: 2021
    detail.hit.zdb_id: 2914332-9
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  • 8
    Online Resource
    Online Resource
    EDP Sciences ; 2022
    In:  RAIRO - Operations Research Vol. 56, No. 3 ( 2022-05), p. 1411-1427
    In: RAIRO - Operations Research, EDP Sciences, Vol. 56, No. 3 ( 2022-05), p. 1411-1427
    Abstract: This study considers a duopoly market in which two competitors operate their own service-inventory systems. Both competitors determine their prices to maximize their profit while considering the inventory holding cost, ordering cost, and cost incurred by lost sales. Customers are price sensitive, and customer attractiveness is expressed by arrival rates. We use a game theory approach to formulate and analyze three types of pricing games: (i) a parallel pricing game, (ii) a sequential pricing game, and (iii) a unified pricing game. The uniqueness of equilibrium prices is analytically proven, after which, a solution procedure for obtaining equilibrium prices is outlined.
    Type of Medium: Online Resource
    ISSN: 0399-0559 , 2804-7303
    RVK:
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2022
    detail.hit.zdb_id: 1468388-X
    SSG: 3,2
    Location Call Number Limitation Availability
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  • 9
    Online Resource
    Online Resource
    EDP Sciences ; 2022
    In:  RAIRO - Operations Research Vol. 56, No. 3 ( 2022-05), p. 1553-1569
    In: RAIRO - Operations Research, EDP Sciences, Vol. 56, No. 3 ( 2022-05), p. 1553-1569
    Abstract: The paper deals with the approximate solving of an inverse problem for the nonlinear delay differential equation, which consists of finding the initial moment and delay parameter based on some observed data. The inverse problem is considered as a nonlinear optimal control problem for which the necessary conditions of optimality are formulated and proved. The obtained optimal control problem is solved by a method based on an improved parallel evolutionary algorithm. The efficiency of the proposed approach is demonstrated through various numerical experiments.
    Type of Medium: Online Resource
    ISSN: 0399-0559 , 2804-7303
    RVK:
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2022
    detail.hit.zdb_id: 1468388-X
    SSG: 3,2
    Location Call Number Limitation Availability
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  • 10
    Online Resource
    Online Resource
    EDP Sciences ; 2022
    In:  RAIRO - Operations Research Vol. 56, No. 3 ( 2022-05), p. 1503-1521
    In: RAIRO - Operations Research, EDP Sciences, Vol. 56, No. 3 ( 2022-05), p. 1503-1521
    Abstract: In this paper, we introduce a novel multi-period data envelopment analysis (MDEA) model that attempts to circumvent the limitations of the existing MDEA models. The proposed global MDEA model is essentially based on major modifications of fundamental DEA axioms to enable a decision making unit (DMU), defined with inputs and outputs of period t , to be evaluated within the production possibility set (PPS) of another period l ,  t  ≠ l. Building on the properties of the global MDEA model, we also introduce a global productivity index, identified as Global Progress and Regress index (GPRI), that render possible the evaluation of a DMU’s extent of progress or regress over multi-period time horizons under variable returns to scale (VRS) production technologies. This lifts the restrictions to two successive periods and constant returns to scale (CRS) of existing productivity indices. The most salient features of the new MDEA model as well as the GPRI are highlighted using an application that involves a real-life sample of 25 bank branches considered over 4 years.
    Type of Medium: Online Resource
    ISSN: 0399-0559 , 2804-7303
    RVK:
    Language: English
    Publisher: EDP Sciences
    Publication Date: 2022
    detail.hit.zdb_id: 1468388-X
    SSG: 3,2
    Location Call Number Limitation Availability
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