Clustering is to group data so that the observations in the same group are more similar to each other than to those in other groups. k-means is a popular clustering algorithm in data mining. Its objective is to optimize the mean squared error (MSE)....
This paper proposes a simple attitude trajectory optimization method to enhance the walking balance of a large-size hexapod robot. To achieve balance motion control of a large-size hexapod robot on different outdoor terrains, we planned the balance a...
We study motif-based optimization for sparse multilayer perceptrons (MLPs), where weights are shared and updated at the level of small neuron groups (‘motifs’) rather than individual connections. Building on Sparse Evolutionary Training (...
Asset-Liability Management (ALM) of banks is defined as simultaneous planning of all bank assets and liabilities under different conditions and its purpose is to maximize profits and minimize the risks in banks by optimizing the parameters in the bal...
To reduce energy consumption in mine ventilation networks under dynamic air demand, this study proposes an Improved Cuckoo Search (ICS) algorithm for energy-efficient airflow regulation. A nonlinear optimization model is established incorporating air...
Constraint-induced movement therapy (CIMT) is one of the most popular treatments for enhancing upper and lower extremity motor activities and participation in patients following a stroke. However, the effect of CIMT on balance is unclear and needs fu...
The Korean government is targeting the development of a renewable energy penetration of 30–35% by 2040 of the total generation. These conditions will decrease network stability due to a lack of inertia, especially in isolated systems, such as J...
The reverse addition process in anti-solvent crystallization is safer and more efficient than sieving when dealing with energetic compounds. A new mathematical model has been developed to understand the crystal size mechanism during the reverse addit...
In recent years, the impact of the energy crisis and environment pollution on quality of life has forced industry to actively participate in the development of a sustainable society. Simultaneously, customer satisfaction improvement has always been a...
China’s urban size distribution has increasingly shifted toward concentration in large cities amid global urbanization and the restructuring of urban development patterns. This trend has intensified governance and spatial pressures in major cit...
In this paper, we propose a new discrete-continuous codification of the Chu–Beasley genetic algorithm to address the optimal placement and sizing problem of the distribution static compensators (D-STATCOM) in electrical distribution grids. The discre...
This single-blind randomized controlled trial investigated the effectiveness of surface electromyography (sEMG)-triggered constraint-induced movement cycling therapy (CIMCT) in improving balance, lower extremity strength, and activities of daily livi...
Comminution–classification circuits are difficult to optimize because hydraulic, granulometric, energy, and economic responses are nonlinearly coupled, while circuit simulation, equipment sizing, simulator benchmarking, and operating optimizati...
Aiming at the multi-constraint three-dimensional bin packing problem for mixed vehicle types in urban logistics, where traditional exact algorithms are limited by NP-hard computational complexity and practical engineering constraints, this study prop...
This study investigates the strategic responses associated with small- and medium-sized enterprise (SME) recovery under crisis conditions. Rather than assuming that maintaining ambidexterity is universally beneficial, it questions whether the balance...
This paper proposes a design methodology that is dedicated to improving the concept of a modular hybrid power chain that uses interleaved converters. The approach involves optimising the system under multi-physical constraints, where the number of ce...
The optimal design of riverbank retaining walls requires a careful balance between structural safety, constructability, and economic efficiency. In this study, a constraint-aware optimization framework is developed for the design of concrete gravity...
Location-based services (LBS) require users to provide their current location for service delivery and customization. Location privacy protection addresses concerns associated with the potential mishandling of location information submitted to the LB...
This paper presents a comprehensive model for optimal energy storage system (ESS) design for an isolated microgrid. The model presented is a mixed integer linear program (MILP) that considers seasonal varying generation (VG) demand, more specifically...
Medical consumable orders are characterized by diverse product types, small batch sizes, frequent orders, and high customization requirements, often leading to inefficient workshop scheduling and difficulties in meeting multiple production constraint...
This article presents an optimized approach to battery sizing and economic dispatch in wind-powered microgrids. The primary focus is on integrating battery depth of discharge (DoD) constraints to prolong battery life and ensure cost-effective energy...
In recent years, hybrid airships have been identified as promising alternatives for high altitude, long endurance missions. In this study, a design methodology to study the feasibility of a winged hybrid airship powered by solar energy is presented....
In two-sided disassembly lines, stations are symmetrically arranged on both sides of the conveyor, which is suitable for large-sized waste products. During the disassembly process, evenly assigning parts to workstations while satisfying various const...
This paper introduces a power-driven systems engineering methodology for the early-phase design of highly miniaturized satellites: PlanarSats. We derive an analytical framework linking power requirements, contingency policies, solar-cell performance,...
This paper presents an optimization method to design a solar water heating (SWH) system based on life cycle cost (LCC). A genetic algorithm is employed to optimize its configuration and sizing as the optimization technique. To ensure that the optimal...
This paper examines whether a compact electron–proton configuration (“small hydrogen”) with a characteristic radius of a few femtometers is excluded by basic relativistic kinematics and simple stationarity constraints. Motivated by...
Wireless sensor networks increasingly support time-critical monitoring applications, where coverage optimization must often be performed under limited computational resources. This work addresses a previously underexplored WSN coverage problem involv...
6 October 2022
Constraint-induced movement therapy (CIMT) has been delivered in the stroke population to improve lower-extremity functions. However, its efficacy on prime components of functional ambulation, such as gait speed, balance, and cardiovascular outcomes,...
Genome-scale stoichiometric modeling methods, in particular Flux Balance Analysis (FBA) and variations thereof, are widely used to investigate cell metabolism and to optimize biotechnological processes. Given (1) a metabolic network, which can be rec...
(1) Background: In various disaster-relief contexts, the demand for resources often exceeds the available supply. Fuzzy optimization approaches address these situations by offering solutions that balance trade-offs between the objective function and...
Background: Inventory planning in retail supply chains requires balancing cost efficiency and service reliability under demand uncertainty and financial limitations. The literature has seldom addressed the joint integration of stochastic demand, dete...
The Dynamic Economic Dispatch (DED) problem underpins the cost-efficient and reliable operation of modern power systems, yet valve-point loading, ramp-rate coupling, and the growing share of intermittent wind, photovoltaic, and pumped-storage hydro (...
The present study addresses a critical issue within the realm of drones: the challenge of distributed constrained optimization. Our research delves into an optimization scenario where the decision variable is confined to a closed convex set. The prim...
The global cruise industry has demonstrated remarkable growth, with modern ships functioning as large-scale floating resorts. Effective food provisioning is a critical operational function that directly impacts both cost efficiency and passenger sati...
Energy storage plays a fundamental role in balancing the power fluctuations induced by the distributed generation of renewable energy sources. In this scenario, electric vehicles can strongly contribute to exchange power with the grid through their o...
Deceptive path planning enables autonomous agents to obscure their true goals from observers by deviating from an expected optimal path. Prior work largely solves full-horizon, end-to-end optimization for single agents, so planning complexity grows w...
Agro-industrial organic wastes differ markedly in moisture, structure, biochemical composition, nutrient value, and contaminant risk, so pretreatment should be selected from the limiting feedstock constraint rather than from a generic technology hier...
The challenges faced by classical supply chain management affect efficiency with regard to business. Classical supply chain management is associated with high risks due to a lack of accountability and transparency. The use of optimization algorithms...
Literature books recommender systems often overlook the vital affective dimensions that dictate reading preferences. To address this, we present an emotion-aware recommendation framework that leverages latent emotional profiles extracted from user re...
The Global Navigation Satellite System (GNSS) has emerged as a critical spatiotemporal infrastructure for ensuring the integrity of remote sensing data links. However, traditional GNSS antenna arrays, typically configured with the antenna spacing of...
An inexact fuzzy multi-objective programming model (IFMOP) based on the environmental carrying capacity is provided for industrial structure optimization problems. In the IFMOP model, both fuzzy linear programming (FLP) and inexact linear programming...
Automated Container Terminals (ACTs) are increasingly challenged by uncertain vessel arrival times, which cause fluctuations in unloading demand and disrupt pre-established yard allocation plans. To address this issue, this study develops a yard allo...
This study presents a practical and scalable framework for the mid- to long-term distribution network planning that reflects real-world infrastructure constraints and investment requirements. While traditional methods often rely on simplified network...
Physics-informed neural networks (PINNs) are gaining traction as surrogate models for fluid dynamics problems, combining machine learning with physics-based constraints. This study investigates the impact of labeled data on the performance of paramet...
The optimal power flow (OPF) is a vital tool for optimizing the control parameters of a power system by considering the desired objective functions subject to system constraints. Metaheuristic algorithms have been proven to be well-suited for solving...
This study introduces a mesoscale modeling methodology for polyurethane-solidified ballast beds (PSBBs) that eliminates reliance on X-ray computed tomography (XCT) and addresses constraints in specimen size, capital cost, and post-processing complexi...
This study investigates how management accounting systems (MASs), specifically the balanced scorecard (BSC) and activity-based costing (ABC), foster organizational ambidexterity (OA) and, in turn, enhance firm performance. Drawing on the resource-bas...
This paper proposes a new hybrid master–slave optimization approach to address the problem of the optimal placement and sizing of distribution static compensators (D-STATCOMs) in electrical distribution grids. The optimal location of the D-STATCOMs i...
This paper introduces a new variant of the Shortest Path Problem (
The issue of limited energy resources is crucial for underwater wireless sensor networks (UWSNs) because these networks operate in remote and harsh environments where access to power sources is limited. Overcoming the energy constraints is necessary...
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