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10th International Conference on Computer and Information Technology

作者： Saber, Ahmed Yousuf Ahmmed, Suman Alshareef, Abdulaziz Abdulwhab, Ahmed Adbullah-Al-Mamun, Khondaker King Abdulaziz Univ Jeddah 21413 Saudi Arabia United Int Univ Dhaka Bangladesh Ahsanullah Univ Sci & Technol Dhaka Bangladesh

ISBN: (纸本)9781424415502

This paper presents a modified particle swarm optimization (MPSO) for constrained non-linear optimization problems. optimization problems are very complex in real life applications. The proposed modified PSO consists of problem (complexity) dependent variable number of promising values (in velocity vector), error-iteration dependent step length, unlocking the dead look of idle particles and so on. It reliably and accurately tracks a continuously changing solution of the complex function and no extra concentration/effort is needed for more complex higher order functions. Constraint management is incorporated in the modified PSO by penalty function. The modified PSO has balance between local and global searching abilities, and an appropriate fitness function helps to converge it quickly. To avoid the method to be frozen, stagnated/idle particles are reset. Finally, benchmark data and methods are used to show the effectiveness of the proposed method.

关键词： modified particle swarm optimization constrained non-linear optimization higher order complex function appropriate fitness function

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constrained non-linear optimization by modified particle swarm optimization

Constrained non-linear optimization by modified particle swa...

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International Conference on Computer and Information Technology (ICCIT)

作者： Ahmed Yousuf Saber Suman Ahmmed Abdulaziz Alshareef Ahmed Abdulwhab Khondaker Adbullah-Al-Mamun King Abdulaziz University Jeddah KSA United International University Dhaka Bangladesh Ahsanullah University of Science and Technology Dhaka Bangladesh

ISBN: (纸本)1424415500;1424415519

关键词： Modified particle swarm optimization constrained non-linear optimization Higher order complex function Appropriate fitness function Particle swarm optimization parametric subharmonic oscillator complex functions Modified step size dependent variables

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Resolution of constrained non-linear optimization problems using direct search methods combined with new measures to admissibility in filters method

Resolution of constrained non-linear optimization problems u...

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International Conference on Control, Artificial Intelligence, Robotics & optimization (ICCAIRO)

作者： Correia, Aldina Matias, Joao Mestre, Pedro Serodio, Carlos P PORTO Polytech Porto ESTG Sch Management & Technol CIICESI Ctr Res & Innovat Business Sci & Informat Porto Portugal

ISBN: (纸本)9781509065363

constrained non-linear optimization problems frequently appears in several areas, from engineering to economics, among others. These problems are usually solved using penalty or barrier methods which construct a sequence of unconstrained problems, which are then solved using unconstrained optimization methods. These methods attempts to minimize the objective function and the constraint violation functions simultaneously, defining a sequence of new objective function which includes information about the objective function and these violations. More recently filters method are used to solve constrained non-linear optimization problems. Filters method, introduced by Fletcher and Leyffer in 2002, have been widely used in several areas of constrained non-linear optimization. These methods deals with this kind of optimization problem as bi-objective, with two functions to minimize: the objective function and a continuous function that aggregates the constraint violation functions. Considering the possibility of information about the derivatives being not accessible, because the objective function and/or the constraints functions of being non smooth, non continuous, non convex and/or with many local minimums then direct search methods must be used in internal processes, in a method as much as in the other. Audet and Dennis in 2004 have presented the first filters method for direct search nonlinear programming, based on pattern search methods. Motivated by this work we have developed a new direct search method, based on simplex methods, for general constrained optimization, that combines the features of the simplex method and filters method, [1] and [2]. This work presents a new variant of these methods which combines the filters method with other direct search methods and are proposed some alternatives to aggregate the constraint violation functions.

关键词： constrained non-linear optimization Filters method direct search methods

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Inverse eigenvalue problem for affinely structured or sparse polynomial matrices with prescribed eigenvalues

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JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 2025年 454卷

作者： Saha, Tanay Mizoram Univ Dept Math & Comp Sci Mizoram India

This paper focuses on addressing the inverse eigenvalue problem associated with affinely structured or sparse polynomial matrices with given distinct eigenvalues. The objective is to characterize all polynomial matrices with the given eigenvalues that possess either a particular affine structure or a sparse structure. Additionally, we aim to determine the minimal structured perturbation required for the coefficient matrices of a given structured polynomial matrix such that the resulting polynomial matrix exhibits the prescribed eigenvalues and is closest to the given polynomial matrix. To tackle this problem, we introduce an optimization-based approach, reformulating the task as a constrained optimization problem. Finally, we present several numerical case studies towards the end of the paper to showcase the effectiveness and practicality of our proposed method. To demonstrate the superiority of our proposed approach, we juxtapose the numerical outcomes with those acquired through the existing methodology documented in the literature.

关键词： Polynomial inverse eigenvalue problem Affinely structured polynomial matrix Sparse polynomial matrix constrained non-linear optimization

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Enhancing Multiobjective Genetic Algorithms for Pharmaceutical Batch Scheduling: A Study on Partitioned Selection with Constraints and Mutation with Greedy Local Search Strategy 34th

Enhancing Multiobjective Genetic Algorithms for Pharmaceutic...

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34th Brazilian Conference on Intelligent Systems

作者： Kohara, Debora T. de Oliveira, Gina M. B. Martins, Luiz G. A. Univ Fed Uberlandia Fac Comp Uberlandia MG Brazil

ISBN: (纸本)9783031790348;9783031790355

Product Manufacturing scheduling or Batch Sequencing (BS) in real-world pharmaceutical manufacturing poses a complex multiobjective optimization challenge, intensified by constraints and uncertain demands. These problems are typically non-linear, may leading to low convergence of feasible solutions, and the computationally intensive evaluation functions may hinder the adoption of certain techniques. Multiobjective Evolutionary Algorithms (MOEAs) have been explored due to their flexible and efficient operators that can be applied to various non-linear multiobjective problems. This study proposes enhancements to MOEA operators, specifically a selection strategy with constraint-based partition for reinsertion to improve diversity and exploration, and a greedy local search strategy incorporated into the mutation operator to enhance the exploitation of the most promising regions. These enhancements were integrated into two models, ps-re and bl-bat, both of which demonstrated significant improvements in the performance metrics compared to a reference model.

关键词： Multiobjective Evolutionary Algorithm constrained non-linear optimization Genetic Algorithms Batch Scheduling

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Joint estimation of Ising model parameters with Hamiltonian constraint

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PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 2024年 633卷

作者： Smirnov, Oliver Columbia Univ Dept Phys New York NY 10027 USA

We propose a new method for the joint estimation of parameters of the 2D Ising model. Our estimation method is the solution to the constrained optimization problem in which the objective function is a pseudo-log-likelihood and the constraint is the Hamiltonian of the external field. We used a series of Monte Carlo simulations with different shapes and sizes of our models to evaluate the behavior of a method without a Hamiltonian constraint and a method with it. We observe that both methods remain consistent with an increased number of parameters and our estimation method tends to deliver a lower variance across all model shapes and sizes compared to a simple pseudo-maximum likelihood.

关键词： Monte Carlo Pseudo-maximum likelihood constrained non-linear optimization

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Linguistic information-based granular computing based on a tournament selection operator-guided PSO for supporting multi-attribute group decision-making with distributed linguistic preference relations

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INFORMATION SCIENCES 2022年 610卷 488-507页

作者： Huang, Ting Tang, Xiaoan Zhao, Shuangyao Zhang, Qiang Pedrycz, Witold Hefei Univ Technol Sch Management Box 270 Hefei 230009 Anhui Peoples R China Minist Educ Key Lab Proc Optimizat & Intelligent Decis Making Hefei 230009 Anhui Peoples R China Minist Educ Engn Res Ctr Intelligent Decis Making Hefei 230009 Anhui Peoples R China Univ Alberta Dept Elect & Comp Engn Edmonton AB T6R 2V4 Canada

This study investigates linguistic information-based granular computing for supporting multi-attribute group decision-making where relative importance of experts/attributes, and outcomes of pairwise comparisons over alternatives are recorded in the form of dis-tributed linguistic preference relations. First, we propose two linguistic information gran-ulation models based on the measures of consistency and consensus to realize the operability of two types of linguistic information, respectively. The granulation of the weight linguistic information is closely linked with that of the alternative preference lin-guistic information in a way that two sets of control factors are introduced. Second, an esti-mation method for expert/attribute weights is developed based on the optimal control factors and solutions to the aforesaid linguistic information granulation models. The pro-posed linguistic information granulation models are in fact constrained non-linear opti-mization problems which may be neither effectively nor efficiently solved by general optimization methods. Third, we therefore propose a novel solution approach named tour-nament selection operator-guided particle swarm optimization (TSOG-PSO). Compared with the standard PSO and its variants, the TSOG-PSO enjoys more feasibility and lower complexity. A new energy vehicle evaluation problem is analyzed using the proposals to demonstrate their applicability. Some discussions and comparative studies are conducted to illustrate the effectiveness of the proposals. (c) 2022 Elsevier Inc. All rights reserved.

关键词： Multi -attribute group decision -making Distributed linguistic preference relation Linguistic information granulation constrained non-linear optimization Particle swarm optimization

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Application of tilt integral derivative control on two-area power system

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JOURNAL OF ENGINEERING RESEARCH 2016年第2期4卷 29-43页

作者： Topno, Pretty Neelam Chanana, Saurabh Natl Inst Technol Dept Elect Engn Kurukshetra 136119 Haryana India

This paper presents a new approach, tilt integral derivative (TID) control, to stabilize frequency variations under load changes in automatic generation control (AGC). The TID control is applied to AGC because of its better response and higher degree of freedom in choosing the control parameters. It has superior qualities such as simple parameter tuning and better disturbance rejection ratio. In addition, it shows insignificant effect of parameter variation on the desired response. To examine these attributes, a two-area thermal system consisting of non-reheat turbine is considered for study. Further, sensitivity analysis has been carried out to explore the robustness of the TID controller. The controller gains are obtained by solving a constrained non-linear optimization using an integral time absolute error (ITAE) index. A comparative analysis between integral control, PID control, fractional order PID (FOPID) control and TID control reveals that TID controller can deliver better performance for AGC.

关键词： Automatic generation control constrained non-linear optimization integral control PID control FOPID control TID control

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Nearest linearly structured polynomial matrix with some prescribed distinct eigenvalues

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linear & MULTIlinear ALGEBRA 2022年第21期70卷 7000-7026页

作者： Saha, Tanay Rakshit, Suman Khare, Swanand R. Indian Inst Technol Dept Math Kharagpur W Bengal India Mankar Coll Dept Math Purba Bardhaman W Bengal India Indian Inst Technol Ctr Excellence Artificial Intelligence Kharagpur W Bengal India

In this paper, we address the problem of computing the nearest linearly structured polynomial matrix with prescribed distinct eigenvalues. The problem deals with the computation of the minimal structured perturbation to the coefficient matrices so that the perturbed polynomial matrix has the prescribed eigenvalues and is the nearest to the given polynomial matrix. In recent years, a series of papers have been published on the perturbation of polynomial matrices with prescribed eigenvalues;however, a linear structure-preserving result does not exist so far to the best of our knowledge. In this paper, we have proposed an optimization based approach where we have reformulated the problem as a constrained optimization problem. Towards the end, a few numerical case studies are presented which demonstrate the efficiency and usefulness of our proposed method.

关键词： Polynomial matrix structured perturbation spectrum of polynomial matrix constrained non-linear optimization

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The implications of re-exports for gravity equation estimation, NAFTA and Brexit

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SPATIAL ECONOMIC ANALYSIS 2019年第4期14卷 384-403页

作者： Lankhuizen, Maureen Thissen, Mark Vrije Univ Amsterdam Dept Spatial Econ Amsterdam Netherlands PBL Netherlands Environm Assessment Agcy The Hague Netherlands

This paper illustrates the importance of taking into account re-exports. It shows that not taking into account re-exports causes estimates from the gravity model to be biased. It also considers the implications of re-exports for two current policy events. It is shown that the United States actually ran a net trade surplus in the North American Free Trade Agreement (NAFTA). Second, it is argued there may be additional costs for the UK economy from Brexit that are not addressed in earlier studies. This paper derives bilateral trade flows corrected for re-exports for a large number of countries at a detailed product level, using the World Input-Output Database (WIOD). Through a constrained non-linear optimization procedure, complete origin-destination matrices of re-exports are determined. Trade is subsequently restored to its most likely origin and destination.

关键词： bilateral trade trade policy re-exports gravity equations Brexit US-Mexico trade North American Free Trade Agreement (NAFTA) World Input-Output Database (WIOD) constrained non-linear optimization

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