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48 articles for “Evolutionary optimization”
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Evolutionary Optimization in MPS: A Brief Review
Abstract: Master production scheduling (MPS) is a combinatorial optimization problem that arises frequently in real-life applications. Because of the complexity and the vast search space, conventional optimization methods such as mathematical programming, dynamic programming and branch-and-bound technique are computationally infeasible. Evolutionary approach-based meta-heuristics have gained prominence in recent years for solving multi-objective optimization problems (MOP). Multi-objective evolutionary approaches (MOEAs) have substantial success across a variety of real-world engineering applications. The present …
Published in Journal of Production Research & Management · Vol. 4, Issue 1, 2014 · pp. 13–21 Read article
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A Study and Performance Evaluation of Evolutionary Optimization Techniques for Multi-objective Master Production Scheduling Problems
Abstract: Master production schedule (MPS) can effectively and efficiently synchronize the operations in any organization. MPS, which is posed as one of the multi-objective parameter optimization problems, is a plan that determines optimal values of products to be produced. For many engineering optimization problems, more competitive and optimal solutions can be obtained by using Heuristic evolutionary optimization algorithms. Among these, two main algorithms considered here are the differential evolution (DE) whose …
Published in Journal of Production Research & Management · Vol. 3, Issue 2, 2013 · pp. 12–22 Read article
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Evolutionary Particle Swarm Optimization (EPSO) based technique considering Voltage Stability Margin for Reactive Power Reserve Optimization
Abstract: Reactive power reserve and voltage stability are one of the important parameters required for proper operation of the electrical power system. Voltage stability covers a broad span of phenomena in power systems and its applications. Voltage stability is defined as ability of power system to assist fixed bearable potential at every single bus of the system under standard operating conditions and when put through to a disturbance. At any instant …
Published in Journal of Power Electronics and Power Systems · Vol. 11, Issue 2, 2021 · pp. 36–41 Read article
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Comparative Performance Analysis of Swarm and Intelligent Evolutionary Techniques for Optimal Design of Distribution Transformer
Abstract: This paper addresses the method of optimal design of a three phase distribution transformer using Genetic Algorithms (GA), Particle Swarm Optimization (PSO) and Teaching-Learning-Based-Optimization Algorithm (TLBO). The design and analysis programs have been developed for constrained optimal design with cost as the objective function. The active part cost of the transformer has been minimized keeping in view BEE (Bureau of Energy Efficiency) standards and constraints. A design example on a …
Published in Trends in Electrical Engineering · Vol. 5, Issue 3, 2015 · pp. 46–58 Read article
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Mathematical Modelling and Comprehensive Review on the Application of Evolutionary Strategies in Design Optimization of Shell and Tube Heat Exchangers
Abstract: This review article presents the application of different evolutionary algorithms which have been utilized for design and optimization of shell and tube heat exchangers in the last decade. The traditional trial and error design approaches can be replaced by such evolutionary algorithms. These evolutionary techniques do not need information of derivatives and hence it can be implemented in various heat exchangers geometry without much complication. Many such EA’s are successfully …
Published in Trends in Mechanical Engineering & Technology · Vol. 7, Issue 3, 2017 · pp. 67–78 Read article
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Isogeometric Topology Optimization of Continuum Structures using Evolutionary Algorithms
Abstract: Isogeometric analysis is a popular method for the analysis of problems involving complex geometry and governed by differential equations. Meta-heuristics are widely used to determine the optimum distribution of material within the given design domain. The focus of this study is to perform isogeometric topology optimization of continuum structures using meta-heuristics nature inspired firefly algorithm. NURBS basis functions are used to construct the geometric model and to calculate the displacements …
Published in Journal of Experimental & Applied Mechanics · Vol. 8, Issue 3, 2017 · pp. 8–18 Read article
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Optimal Allocation of FACTS Devices Using Quantum Inspired Evolutionary Programming
Abstract: Quantum Inspired Evolutionary Programming (QIEP) is an optimization technique that combines the benefits of quantum computing and evolutionary algorithms together. In this paper this technique is used to find optimal allocation of Flexible AC Transmission System (FACTS) devices. The results are compared with the results found from genetic algorithms (GAs). Based on the results it can be concluded that QIEP technique is better than GAs. Keywords: QIEP, quantum computing, evolutionary …
Published in Trends in Electrical Engineering · Vol. 5, Issue 1, 2015 · pp. 23–27 Read article
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Parallel Search Engines for Topology Optimization of an Arch Truss using Evolutionary Algorithms
Abstract: The use of parallel search engines to solve NP-Hard problems is increasingly in use with the computational power becoming more economical. The objective of this paper is to effectively explore and exploit the search domain to identify the optimal point using two search engines in parallel. This paper proves that intensification and diversification can be performed effectively using two search engines in parallel. The use of two search engines in …
Published in Recent Trends in Civil Engineering & Technology · Vol. 7, Issue 2, 2017 · pp. 22–27 Read article
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Machine Learning-Assisted Design and Optimization of Lightweight Polymer Composites for IoT-Enabled Automotive Applications
Abstract: This study aims to develop an integrated machine learning and optimization framework for the intelligent design of lightweight polymer composites suited for IoT-enabled automotive applications. The goal is to enhance material performance while satisfying multiple design constraints such as mechanical strength, thermal stability, and process compatibility. A curated dataset of polymer composite formulations was used to train a Random Forest Regression (RFR) model capable of predicting tensile strength, thermal conductivity, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 12–27 Read article
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AI-Enabled Optimization of Additively Manufactured Composite Materials for Enhanced Mechanical and Thermal Performance
Abstract: This paper discusses the optimization of multi-objective optimization of enhanced coupling of heat and mechanical properties of 3D printed polymer composite materials by artificial intelligence (AI), as a component of a multi-objective optimization framework. It aims at development of nonlinear printing parameters and material properties relationships to achieve maximum tensile strength and thermal conductivity in polymer composites produced through fused deposition modeling (FDM). Short carbon fiber reinforcement was used to …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 867–891 Read article
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Accelerating Unsupervised Feature Learning: Parallelized Training of Denoising Autoencoders
Abstract: Unsupervised representation learning has become a cornerstone of contemporary machine learning, enabling algorithms to extract informative features from un-labelled, high-dimensional data. This work investigates the efficacy of stacked denoising autoencoders (SDAEs) trained via parallelized stochastic gradient descent (SGD) as a scalable approach to feature extraction. By strategically leveraging multi-threaded computation, our study systematically examines the trade-offs between increased parallelism, training efficiency, and the preservation of model accuracy. Experiments on the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 56–64 Read article
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Hybrid Intelligent Controllers for Highly Accurate Trajectory Tracking of Manipulator
Abstract: Due to the lack of accurate knowledge of robotic manipulator model, the highly precise trajectory tracking cannot be obtained. Moreover in these modern times, multiple design control objectives cannot be met by single controller, hence; there is a need for having two or more controllers at a time. Hence, more powerful and effective systems can be made by combining these intelligent controllers. In this regard, evolutionary optimized advance intelligent controller …
Published in Trends in Electrical Engineering · Vol. 7, Issue 3, 2017 · pp. 17–30 Read article
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Speed Control of PMSM using Optimization Methods
Abstract: AbstractThis paper represents a modelling and optimized design of speed control for a permanent magnet synchronous motor (PMSM). The PI controller of inner current loop is optimized using evolutionary algorithm like Particle Swarm Optimization (PSO) method. To illustrate effect of proposed method, the performance of evaluationary algorithm is compared with traditional optimization method i.e., Ziegler-Nichols method. The main objective of the proposed work are, develop mathematical modelling of PMSM motor …
Published in Journal of Microcontroller Engineering and Applications · Vol. 6, Issue 2, 2019 · pp. 8–16 Read article
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Genetic Algorithm Application for Efficient Load Frequency Control
Abstract: Load frequency control (LFC) is known to be significant control strategy for operation in electric power grid that entails balancing the electrical power provided by power plants with the electrical power consumed by the load. The primary purpose of LFC is to ensure that the power system functions within a specific frequency range and that the power provided by power plants matches the power used by the load. Power system …
Published in Journal of Control & Instrumentation · Vol. 14, Issue 3, 2023 · pp. 1–14 Read article
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Optimization of Biohybrid Polymer Synthesis Using Fuzzy Inference Systems
Abstract: This investigation proposes a methodology to optimize biohybrid polymer synthesis using fuzzy inference systems (FIS). The study combines fuzzy logic principles with mathematical calculations for finding the best synthesis parameters to enhance the synthesis quality. This study consists on a sample about the use of FIS on optimisation of polymer synthesis, where they show the process of fuzzification, rule base creation, inference mechanism and defuzzification using the centroid method through …
Published in Journal of Polymer & Composites · Vol. 12, Issue 5, 2024 · pp. 36–47 Read article
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The Coordinated Approach for Reactive Power Management of Deregulated Electricity Market
Abstract: RPM is an important ancillary service, especially in deregulated energy environment which contains two major areas: reactive power purchase and reactive power dispatch. Various technical and economic issues need to be considered in this market. This work shows RPD as the main optimization problem. As optimized electric power dispatch is important problem in electrical power systems. Cost infimumization, voltage stability improvement, losses minimization, and terminal voltage deviation minimization are important …
Published in Journal of Power Electronics and Power Systems · Vol. 9, Issue 2, 2019 · pp. 5–14 Read article
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Design of Differential Evolution Optimized PI Controller for a Temperature Process
Abstract: Differential evolution is a new stochastic population-based optimization algorithm. It is an accurate, fast and robust optimization method. In this paper, a PI controller is used and differential evolution optimization technique is used to optimize the controller parameters. The robust controller parameters are obtained by solving the optimization problem, which consists of objective functions and constraints, using differential evolution method. Here differential evolution is implemented in tuning of a PI …
Published in Journal of Control & Instrumentation · Vol. 3, Issue 1-3, 2012 · pp. 17–26 Read article
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Numerical Simulation of Hybrid GSA Based Optimal Power Flow for Multi Objective Optimization Strategy
Abstract: Restricted nonlinear optimization in electric power systems engineering is a topic of Optimal Power Flow (OPF) that has been extensively investigated. It has been a long and remarkable history for the OPF, which was founded in the 1960s, of research and publication. Newcomers to OPF research face a challenging undertaking since there is so much information available and because OPF's popularity within the electric power systems community has prompted authors …
Published in Journal of Instrumentation Technology & Innovations · Vol. 11, Issue 3, 2021 · pp. 24–32 Read article
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Generation Scheduling Using Quantum Inspired Evolutionary Programming
Abstract: A new novel evolutionary algorithm based on principles of quantum mechanics known as quantum inspired evolutionary programming (QIEP) has emerged as a modern optimization technique. QIEP is unique than other evolutionary programming for its qubit representation and superposition of states. QIEP has proven its applicability in different combinatorial problems successfully. It can also be applied in power system optimization problem. In this paper, we have used QIEP for generation scheduling. …
Published in Trends in Electrical Engineering · Vol. 5, Issue 1, 2015 · pp. 12–15 Read article
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Optimization of ED Problems of Interconnected Power System Using Particle Swarm Optimization
Abstract: This paper proposes an effective and useful evolutionary-based method to solve the economic load dispatch (ELD) problem. This paper introduces particle swarm optimization (PSO) technique for solving the economic dispatch (ED) problem in power system. ELD problem is really the solution of a large number of load flow problem with equality & inequality constraints. In this paper, a PSO technique for solving the ELD problem in power system is proposed. …
Published in Journal of Power Electronics and Power Systems · Vol. 5, Issue 1, 2015 · pp. 1–8 Read article