Ensemble Differential Evolution with Simulation-Based Hybridization and Self-Adaptation for Inventory Management Under Uncertainty DOI Creative Commons
Sarit Maitra, Vivek Mishra,

Sukanya Kundu

et al.

arXiv (Cornell University), Journal Year: 2023, Volume and Issue: unknown

Published: Jan. 1, 2023

This study proposes an Ensemble Differential Evolution with Simula-tion-Based Hybridization and Self-Adaptation (EDESH-SA) approach for inven-tory management (IM) under uncertainty. In this study, DE multiple runs is combined a simulation-based hybridization method that includes self-adaptive mechanism dynamically alters mutation crossover rates based on the success or failure of each iteration. Due to its adaptability, algorithm able handle complexity uncertainty present in IM. Utilizing Monte Carlo Simulation (MCS), continuous review (CR) inventory strategy ex-amined while accounting stochasticity various demand scenarios. enables realistic assessment proposed algo-rithm's applicability resolving challenges faced by IM practical settings. The empirical findings demonstrate potential im-prove financial performance optimize large search spaces. makes use testing Ackley function Sensitivity Analysis Perturbations investigate how changes variables affect objective value. analysis provides valuable insights into behavior robustness algorithm.

Language: Английский

Flash flood susceptibility modeling using optimized deep learning method in the Uttarakhand Himalayas DOI
Mohd Rihan, Javed Mallick,

Intejar Ansari

et al.

Earth Science Informatics, Journal Year: 2024, Volume and Issue: 18(1)

Published: Dec. 11, 2024

Language: Английский

Citations

3
A multi-leader Harris hawks optimizer with adaptive mutation and its application for modeling of silicon content in liquid iron of blast furnace DOI
Zhendong Liu, Yiming Fang, Le Liu

et al.

Mathematics and Computers in Simulation, Journal Year: 2023, Volume and Issue: 213, P. 466 - 514

Published: July 5, 2023

Language: Английский

Citations

8
Dynamic Harris hawks optimizer based on historical information and tournament strategy and its application in numerical optimization of blast furnace ingredients DOI
Zhendong Liu, Yiming Fang, Le Liu

et al.

Applied Soft Computing, Journal Year: 2024, Volume and Issue: 164, P. 111976 - 111976

Published: July 10, 2024

Language: Английский

Citations

2
A robot path planning method using improved Harris Hawks optimization algorithm DOI Creative Commons
Changyong Li, Qing Si, Jianan Zhao

et al.

Measurement and Control, Journal Year: 2023, Volume and Issue: 57(4), P. 469 - 482

Published: Oct. 28, 2023

The traditional Harris Hawks optimization algorithm is prone to the local shortest path, slow search speed and poor path accuracy in indoor mobile robot planning. For above problems, a multi-strategy improvement of (MIHHO) proposed. In this study, Chebyshev chaotic mapping strategy used increase diversity Hawk population, improve global performance algorithm, prevent being trapped locally optimal path. A fusion exploration mechanism proposed fuse discovery sparrow with HHO. Then influence factor E improved algorithm’s efficiency, finally, design dynamic Lévy flight strategy, which accelerates convergence improves planning speed. Simulation results show that MIHHO method exhibits better planning, superior quality planned paths.

Language: Английский

Citations

6
Sizing of Microgrid System Including Multi-Functional Battery Storage and Considering Uncertainties DOI Creative Commons
Ibrahim M. Ibrahim, Almoataz Y. Abdelaziz, Hassan Haes Alhelou

et al.

IEEE Access, Journal Year: 2023, Volume and Issue: 11, P. 29521 - 29540

Published: Jan. 1, 2023

Battery storage units (BSUs) are usually used to perform a single function in most planning studies related microgrids (MGs). This paper presents an effective methodology use the BSUs multi-function including supply/demand matching and energy arbitrage. is done according system policy containing all possible scenarios fully utilize maximize benefit. In proposed work, optimal sizing of MG under study wind turbines (WTs), photovoltaic (PV), BSUs, diesel (DUs) obtained. The main objectives are; 1) minimizing total costs MG, 2) harmful gas emissions, 3) accumulated power difference between generation from renewable systems (RESs) demand. Due stochastic behavior output RESs, uncertainties speed, solar irradiance, temperature considered study. Two modes operation (grid-connected islanded) demand side management (DSM) also considered. problem formulated as constrained nonlinear optimization solved using two metaheuristic algorithms, Moth-Flame Optimization (MFO) Hybrid Firefly Particle Swarm (HFPSO). Moreover, different parameters by Latin Hypercube Sampling (LHS) method generate samples temperature. To examine methodology, case presented discussed. results MFO HFPSO, compared show their effectiveness solving assure solution. implemented MATLAB software.

Language: Английский

Citations

5
Improving Wild Horse Optimizer: Integrating Multistrategy for Robust Performance across Multiple Engineering Problems and Evaluation Benchmarks DOI Creative Commons
Lei Chen, Yikai Zhao, Yunpeng Ma

et al.

Mathematics, Journal Year: 2023, Volume and Issue: 11(18), P. 3861 - 3861

Published: Sept. 10, 2023

In recent years, optimization problems have received extensive attention from researchers, and metaheuristic algorithms been proposed applied to solve complex problems. The wild horse optimizer (WHO) is a new algorithm based on the social behavior of horses. Compared with popular algorithms, it has excellent performance in solving engineering However, still suffers problem insufficient convergence accuracy low exploration ability. This article presents an improved (I-WHO) early warning competition mechanisms enhance algorithm, which incorporates three strategies. First, random operator introduced improve adaptive parameters search algorithm. Second, strategy position update formula increase population diversity during grazing. Third, selection mechanism added, agent updated multimodal at exploitation stage this article, 25 benchmark functions (Dim = 30, 60, 90, 500) are tested, complexity I-WHO analyzed. Meanwhile, compared six verified by Wilcoxon signed-rank test four real-world experimental results show that significantly accuracy, showing preferable superiority stability.

Language: Английский

Citations

5
Daily runoff prediction during flood seasons based on the VMD–HHO–KELM model DOI Creative Commons
Xianqi Zhang, Fang Liu, Qiuwen Yin

et al.

Water Science & Technology, Journal Year: 2023, Volume and Issue: 88(2), P. 468 - 485

Published: July 15, 2023

Improving the accuracy of daily runoff in lower Yellow River is important for flood control and reservoir scheduling River. Influenced by factors such as meteorology, climate change, human activities, series present non-stationary non-linear characteristics. To weaken non-linearity non-smoothness time improve prediction, a new combined prediction model (VMD-HHO-KELM) based on ensemble Variational Modal Decomposition (VMD) algorithm Harris Hawk Optimisation (HHO) algorithm-optimised Kernel Extreme Learning Machine (KELM) proposed applied to Gaocun Lijin hydrological stations. The VMD-HHO-KELM has highest accuracy, with R2 reaching 0.95, mean absolute error 13.3, root square 33.83 at station, 0.96, 8.03, 38.45 station.

Language: Английский

Citations

4
A Comparative Study on Different Optimization Algorithms for Solving Economic Dispatch Problem DOI
Tareq Foqha, Samer Alsadi, Shady S. Refaat

et al.

Published: Jan. 8, 2024

Economic dispatch is one of the mathematical optimization problems in power system operation and planning. It aims to find most efficient output for generating units that meets demand load at lowest possible cost while satisfy all operational constraints. This paper examines numerous methods address economic problem, including deterministic approaches like Lagrange multiplier method, metaheuristic algorithms such as Genetic Algorithm, Firefly Harris-Hawks algorithm, their hybridizations. The study also utilizes PowerWorld Simulator, a software package solves using sequential linear programming. Two different case studies have been conducted on IEEE 5-bus 30-bus test systems demonstrating effectiveness proposed algorithms. results various showed are effective solving problem. was shown hybrid algorithms, which combine strengths techniques, can achieve significant enhancement total compared conventional methods.

Language: Английский

Citations

1
Compound improved Harris hawks optimization for global and engineering optimization DOI
Chengtian Ouyang, Liao Chang, Donglin Zhu

et al.

Cluster Computing, Journal Year: 2024, Volume and Issue: 27(7), P. 9509 - 9568

Published: April 24, 2024

Language: Английский

Citations

1
A mixed Harris hawks optimization algorithm based on the pinhole imaging strategy for solving numerical optimization problems DOI
Liang Zeng, Yanyan Li, Hao Zhang

et al.

The Journal of Supercomputing, Journal Year: 2023, Volume and Issue: 79(14), P. 15270 - 15323

Published: April 16, 2023

Language: Английский

Citations

3