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Nanophotonics, which explores significant light–matter interactions at the nanoscale, has facilitated significant advancements across numerous research fields. A key objective in this area is the design of ultra-compac...

This clearly written , mathematically rigorous text includes a novel algorithmic exposition of the simplex method and also discusses the Soviet ellipsoid algorithm for linear programming; efficient algorithms for network...

Abstract Background The residential building sector is a major contributor to Germany’s greenhouse gas emissions. Over 60 % of the energy used for space and domestic hot water heating comes from fossil fuels sources a...

Abstract The Purpose of this research is the development Direct Search Methods for minimizing the objective function; The Developed Methods reduces the approach time to the minimum through two techniques: 1) by reducing...

Abstract The computation of optimal routes considering multiple factors is a key challenge in operations research, with significant impact on practical decision-making and real-world efficiency. Optimal bus transit route...

Metaheuristics Algorithms are widely recognized as one of most practical approaches for Combinatorial Optimization Problems. This paper presents a comparison between two metaheuristics to solve a problem of Phase Bal...

Abstract In this paper, it is presented a general optimization methodology for improving empirical models predicting Okumura-Hata, Cost-231, ECC-33, and Egli using Genetic and Differential Evolution Algorithms. The metho...

Tardiness related objectives are of utmost importance in production systems when client satisfaction is a main goal of a company. These objectives measure the system response to the client requirements and rate manager´...

From the Publisher: This book brings together - in an informal and tutorial fashion - the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic al...

In trying to solve multiobjective optimization problems, many traditional methods scalarize the objective vector into a single objective. In those cases, the obtained solution is highly sensitive to the weight vector use...

In previous works the ability of CPS-MCPC (an evolutionary, co-operative, population search method with multiple crossovers per couple) to build well delineated Pareto fronts in diverse multiobjective optimization proble...

Abstract An increasing number of researchers have researched fixture layout optimization for thin-walled part assembly during the past decades. However, few papers systematically review these researches. By analyzing exi...

Abstract This paper presents a model that uses bio-inspired optimization algorithms to control of the mutual coupling (MC) in Multiple-Input Multiple-Output (MIMO) systems. The method promotes an increase in the channel ...

In this work, we investigate the effects of estimation uncertainties in the optimization of the optical signal-to-noise ratio (OSNR) at the wavelength division multiplexing (WDM) optical networks. The OSNR optimization i...

Regression testing plays a critical role in ensuring the reliability and quality of software following continuous integration and development. However, executing all test cases during regression testing can be time-consu...

To date, various optimization algorithms have been used to design non-intuitive photonic structures with unconventional optical performance. Good training datasets facilitate the optimization process, particularly when a...

To address the issues of low solution accuracy, premature convergence, and susceptibility to local optima in the Parrot Optimization (PO) algorithm, a Reinforced Multi-strategy Parrot Optimization (RMPO) algorithm has be...

The high population growth rate, the accelerated industrialization and unpredictability of oil prices in the world have considerably raised the energy demand which has enhanced the necessity of alternative and sustainabl...

This paper proposes an innovative automated multiphysics Microelectromechanical systems (MEMS) co-optimization platform integrating the embedded reduced-order modeling offered by Coventor MEMS+ with MATLAB’s numerical ...

Abstract The Broad Learning System (BLS) provides an effective framework for nonlinear mapping, offering advantages over traditional deep neural networks through its expanded input node architecture. While BLS has demons...

On-demand ride services or ride-sourcing services have been experiencing fast development and steadily reshaping the way people travel in the past decade. Various optimization algorithms, including reinforcement learning...

A wall jet is a typical flow field encountered in various engineering fields, including the deviation tunnels, the bottom outlets of dams, and wastewater treatment. Appropriate prediction of wall jet characteristics is h...

Ant Colony Optimization algorithms are intrinsically distributed algorithms where independent agents are in charge of building solutions. Stigmergy or indirect communication is the way in which each agent learns from the...

Rough Sets Theory has opened new trends for the development of the Incomplete Information Theory. Inside this one, the notion of reduct is a very significant one, but to obtain a reduct in a decision system is an expensi...