Giant Pacific octopus optimizer based on fitness-distance balance and natural survival method to solve time-cost-quality-labor trade-off problem in construction projects

International Journal of Management Science and Engineering Management, Год журнала: 2025, Номер unknown, С. 1 - 18

Опубликована: Янв. 21, 2025

Язык: Английский

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Applying a Hybrid Gray Wolf‐Enhanced Whale Optimization Algorithm to the Capacitated Vehicle Routing Problem

Journal of Advanced Transportation, Год журнала: 2025, Номер 2025(1)

Опубликована: Янв. 1, 2025

The study presents a novel hybrid gray wolf and whale optimization algorithm (hGWOAM) for the capacitated vehicle routing problem (CVRP). By integrating enhanced (EWOA) optimizer (GWO) with tournament selection, opposition‐based learning, mutation techniques, hGWOAM enhances efficiency under capacity constraints. Computational evaluations demonstrate its superior performance, achieving lower percentage deviations (%dev) compared to existing algorithms across multiple case studies real‐world applications. In Case Study 1, achieved mean deviation than EWOA (0.89%), GWO (0.74%), SCA (0.59%), DA (1.63%), ALO (2.26%), MHPSO (1.85%), PSO (1.96%), DPGA (2.85%), SGA (4.14%). 2, outperformed (12.05%), (2.53%), (21.07%), (17.58%). application, it best %dev, surpassing (6.64%), (6.34%), (9.01%), (12.24%). These findings highlight hGWOAM’s potential optimizing logistics, reducing operational costs, minimizing environmental impact while also paving way future advancements in metaheuristic optimization.

Язык: Английский

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Study on the optimization of duration for repetitive projects considering spatial interference effects in operations

Journal of Asian Architecture and Building Engineering, Год журнала: 2025, Номер unknown, С. 1 - 26

Опубликована: Апрель 22, 2025

Язык: Английский

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Enhancing efficiency in delivering petroleum products: optimizing the deteriorating inventory-routing problem with heterogeneous multi-compartment vehicles

International Journal of Management Science and Engineering Management, Год журнала: 2024, Номер unknown, С. 1 - 24

Опубликована: Ноя. 10, 2024

The Petrol Station Replenishment Problem (PSRP) is a complex logistical challenge that involves several factors, including multi-compartment vehicles of different types, multiple returns to the depot(s), and evaporation losses. This research proposes Deteriorating Inventory-Routing (DIRP) approach solve PSRP, optimize routing costs, minimize losses, inventory levels. study uses Mixed Integer Non-Linear Programming (MINLP) model takes into account vehicle scheduling, allowing petrol stations be replenished times during depot's working hours depending on their consumption rate. amount at monitored throughout period, not just beginning end. proposed Genetic Algorithm Tabu Search (GATS) Greedy sub-algorithms (GAG) are tested small large instances DIRP. results show GATS algorithm produces optimal solutions for most compared best values obtained, while GAG provides satisfactory problems with reasonable computation time reduces improving objective function value problems. For datasets, surpasses by 4.45% in best-known solution and, average, 8.81% lower mean-known solution.

Язык: Английский

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Research on Applying Machine Learning Models to Predict and Assess Return on Assets (Roa)

Research Square (Research Square), Год журнала: 2024, Номер unknown

Опубликована: Март 22, 2024

Abstract Return on Assets (ROA), a profitability measure, is crucial in corporate finance for assessing how efficiently company uses assets to generate profit. Currently, the prediction of ROA index at present tedious, manual process. It usually involves making educated guesses or waiting accurate data, which becomes available only after financial reports have been compiled. This paper introduces machine learning model predicting index. The draws data from 78 companies listed Vietnam Stock Exchanges (HOSE and HNX) over span 2012 2022.The Random Forest (RF) was put test using datasets selected Vietnamese businesses 2023. results demonstrated high level precision, with an error rate less than 1%, R2 value 0.9762, Root Mean Square Error (RMSE) 0.5826. These findings indicate potential real-world boosting business performance. In conclusion, integration analysis represents substantial progress. enhances both accuracy efficiency holds promise future advancements management practices. study aims encourage more research development this area, leading advanced efficient tools.

Язык: Английский

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Research on applying machine learning models to predict and assess return on assets (ROA)

Asian Journal of Civil Engineering, Год журнала: 2024, Номер 25(5), С. 4269 - 4279

Опубликована: Апрель 27, 2024

Язык: Английский

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Optimizing beyond boundaries: empowering the salp swarm algorithm for global optimization and defective software module classification

Neural Computing and Applications, Год журнала: 2024, Номер 36(30), С. 18727 - 18759

Опубликована: Июль 31, 2024

Язык: Английский

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