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Having developed multiobjective optimization algorithms using evolutionary optimization methods and demonstrated their niche on various practical problems involving mostly two and three objectives, there is now a growing...

A framework is developed to explore the connection between effective optimization algorithms and the problems they are solving. A number of "no free lunch" (NFL) theorems are presented which establish that for any algori...

In this paper, we solve some benchmarks of Set Covering Problem and Equality Constrained Set Covering or Set Partitioning Problem. The resolution techniques used to solve them were Ant Colony Optimization algorithms and ...

This work proposes a numerical procedure to simulate and optimize the thermal response of a multilayered wallboard system for building envelopes, where each layer can be possibly made of Phase Change Materials (PCM)-base...

Abstract The present work aims at the application of different optimization strategies in the electromagnetic analysis of the Variable Reluctance Motor (VRM) through Finite Element (FE) simulation. Two case studies are i...

Liquid air energy storage (LAES) systems are a promising technology for storing electricity due to their high energy density and lack of geographic constraints. However, some LAES systems still have relatively low round-...

Abstract Background Optimization of biotechnological processes is traditionally limited by time-consuming trial-and-error approaches and the complexity of simultaneously optimizing multiple, often conflicting objectives....

Abstract The self-scaling VM-algorithms solves an unconstrained non-linear optimization problems by scaling the Hessian approximation matrix before it is updated at each iteration to avoid the possible large eigen-values...

Liquid Air Energy Storage offers several advantages over other energy storage systems, including high energy density, scalability, cost-competitiveness, and non-geographical constraints. This study develops a computation...

Cloud computing environments face persistent structural challenges in cost control, dynamic resource allocation, and security risk management, which traditional infrastructure approaches fail to address adequately. This ...

In this article we present an algorithm for solving bound constrained optimization problems without derivatives based on Powell´s method [38] for derivative-free optimization. First we consider the unconstrained optimiz...

This study compares seven quantum algorithms—Variational Quantum Eigensolver (VQE), Variational Quantum Deflation (VQD), Quantum Approximate Optimization Algorithm (QAOA), Quantum Amplitude Estimation (QAE), Quant...

Abstract This paper presents a cloud-based data-driven design optimization system, named DADOS, to help engineers and researchers improve a design or product easily and efficiently. DADOS has nearly 30 key algorithms, in...

Abstract Current research on autonomous mobile robots focuses primarily on perceptual accuracy and autonomous performance. In commercial and domestic constructions, concrete, wood, and glass are typically used. Laser and...

Abstract Blank holder force (BHF) is a crucial parameter in deep drawing, having close relation with the forming quality of sheet metal. However, there are different BHFs maintaining the best forming effect in different ...

Abstract Inventory management is a core part of supply chains, and over the years it has been increasingly challenged by the need to balance economic performance with environmental considerations. While prior reinforceme...

We show that deep generative neural networks, based on global optimization networks (GLOnets), can be configured to perform the multiobjective and categorical global optimization of photonic devices. A residual network s...

Abstract In response to the dual challenges of complex static obstacles and frequent dynamic disturbances in the construction site environment, this paper proposes a hybrid path planning strategy that integrates global s...

Introduction. Metaheuristic algorithms are effective for solving complex power system optimization problems characterized by nonlinearity, multimodality, and high dimensionality. Nature-inspired strategies based on adapt...

Abstract Multiple-input multiple-output non-orthogonal multiple access (MIMO-NOMA) systems assisted by reconfigurable intelligent surfaces (RIS) have become a viable way to improve next-generation wireless networks. Howe...

BDA is an adaptation of Dragonfly Algorithm (DA) that optimizes computation for single-objective, discrete, and multi-objective problems. Combining BDA optimization algorithm with KNN and SVM classification algorithms ai...

Abstract Background Protein-protein interaction (PPI) network-based protein function prediction algorithms, which use the guilt-by-association principle, are widely applied in medical and human domains, but they are comp...

Abstract Active power distribution networks are evolving with the integration of distributed energy resources (DERs) and advanced optimization techniques to enhance grid flexibility and efficiency. However, radial distri...

This study develops an innovative framework for the multi-objective optimization of multi-channel supply chains under uncertainty. The framework integrates the D-number model, an extension of Dempster–Shafer Theory (DS...