Wolf-Bird Optimizer (WBO): A Novel Metaheuristic Algorithm for Building Information Modeling-based Resource Tradeoff DOI Creative Commons
Mahdi Azizi, Milad Baghalzadeh Shishehgarkhaneh, Mahla Basiri

et al.

Journal of Engineering Research, Journal Year: 2023, Volume and Issue: unknown

Published: Nov. 1, 2023

In the animal kingdom, a mutually-beneficial ecosystemic coexistence and partnership in predation between wolves ravens, known as wolf-bird relationship, is observed various cultures. The Wolf-Bird Optimizer (WBO), novel metaheuristic algorithm inspired by this natural zoological proposed. This method developed based on foraging behaviors of ravens wolves, wherein intelligence finding prey sending signals to for assistance hunting considered. Furthermore, framework resource tradeoffs project scheduling using algorithms Building Information Modeling (BIM) approach established research. For statistical analysis, are independently run 30 times with preset stopping condition, enabling calculation descriptive metrics such mean, standard deviation (SD), required number objective function evaluations. To ensure significance results, several inferential methods, including Kolmogorov-Smirnov, Wilcoxon, Mann-Whitney, Kruskal-Wallis tests, employed. Additionally, capability proposed solving tradeoff problems four construction projects assessed. performance WBO also evaluated two benchmark projects, results indicating algorithm's ability produce competitive exceptional outcomes regarding tradeoffs.

Language: Английский

A comparison performance analysis of eight meta-heuristic algorithms for optimal design of truss structures with static constraints DOI Creative Commons
Nima Khodadadi, Aybike Özyüksel Çiftçioğlu, Seyedali Mirjalili

et al.

Decision Analytics Journal, Journal Year: 2023, Volume and Issue: 8, P. 100266 - 100266

Published: June 16, 2023

Metaheuristics have been successfully used for solving complex structural optimization problems. Many algorithms are proposed truss structure size and shape under some constraints. This study considers eight population-based meta-heuristic methods: African Vultures Optimization Algorithm (AVOA), Flow Direction (FDA), Arithmetic (AOA), Generalized Normal Distribution (GNDO), Stochastic Paint Optimizer (SPO), Chaos Game (CGO), Crystal Structure (CRY) Material Generation (MGO). These meta-heuristics methods to optimize the of three aluminum structures. aims reduce weight members while meeting a set displacement stress The performance these is assessed by optimizing well-known benchmarks results show that (SPO) outperforms other in terms accuracy convergence rate.

Language: Английский

Citations

23
Multi-objective generalized normal distribution optimization: a novel algorithm for multi-objective problems DOI Creative Commons
Nima Khodadadi, Ehsan Khodadadi, Benyamın Abdollahzadeh

et al.

Cluster Computing, Journal Year: 2024, Volume and Issue: 27(8), P. 10589 - 10631

Published: May 8, 2024

Abstract This study introduces the Multi-objective Generalized Normal Distribution Optimization (MOGNDO) algorithm, an advancement of (GNDO) now adapted for multi-objective optimization tasks. The GNDO previously known its effectiveness in single-objective optimization, has been enhanced with two key features optimization. first is addition archival mechanism to store non-dominated Pareto optimal solutions, ensuring a detailed record best outcomes. second enhancement new leader selection mechanism, designed strategically identify and select solutions from archive guide process. positions MOGNDO as cutting-edge solution setting benchmark evaluating performance against leading algorithms field. algorithm's rigorously tested across 35 varied case studies, encompassing both mathematical engineering challenges, benchmarked prominent like MOPSO, MOGWO, MOHHO, MSSA, MOALO, MOMVO, MOAOS. Utilizing metrics such Generational Distance (GD), Inverted (IGD), Maximum Spread (MS), underscores MOGNDO's ability produce fronts high quality, marked by exceptional precision diversity. results affirm superior versatility, not only theoretical tests but also addressing complex real-world problems, showcasing convergence coverage capabilities. source codes algorithm are publicly available at https://nimakhodadadi.com/algorithms-%2B-codes .

Language: Английский

Citations

12
An Archive-Based Multi-Objective Arithmetic Optimization Algorithm for Solving Industrial Engineering Problems DOI
Nima Khodadadi, Laith Abualigah,

El-Sayed M. El-kenawy

et al.

IEEE Access, Journal Year: 2022, Volume and Issue: 10, P. 106673 - 106698

Published: Jan. 1, 2022

This research proposes an Archive-based Multi-Objective Arithmetic Optimization Algorithm (MAOA) as alternative to the recently established (AOA) for multi-objective problems (MAOA). The original AOA approach was based on distribution behavior of vital mathematical arithmetic operators, such multiplication, division, subtraction, and addition. idea archive is introduced in MAOA, it may be used find non-dominated Pareto optimum solutions. proposed method tested seven benchmark functions, ten CEC-2020 mathematic eight restricted engineering design challenges determine its suitability solving real-world difficulties. experimental findings are compared five optimization methods (Multi-Objective Particle Swarm (MOPSO), Slap (MSSA), Ant Lion Optimizer (MOALO), Genetic (NSGA2) Grey Wolf (MOGWO) reported literature using multiple performance measures. empirical results show that MAOA outperforms existing state-of-the-art approaches has a high convergence rate.

Language: Английский

Citations

37
A multi-objective Chaos Game Optimization algorithm based on decomposition and random learning mechanisms for numerical optimization DOI

Salma Yacoubi,

Ghaith Manita, Amit Chhabra

et al.

Applied Soft Computing, Journal Year: 2023, Volume and Issue: 144, P. 110525 - 110525

Published: June 15, 2023

Language: Английский

Citations

21
Multi-objective optimal allocation of multiple capacitors and distributed generators considering different load models using Lichtenberg and thermal exchange optimization techniques DOI Creative Commons
Mohamed A. Elseify, Salah Kamel, Loai Nasrat

et al.

Neural Computing and Applications, Journal Year: 2023, Volume and Issue: 35(16), P. 11867 - 11899

Published: Feb. 8, 2023

Abstract Integrating distributed generations (DGs) into the radial distribution system (RDS) are becoming more crucial to capture benefits of these DGs. However, non-optimal integration renewable DGs and shunt capacitors may lead several operational challenges in systems, including high energy losses, poor voltage quality, reverse power flow, lower stability. Therefore, this paper, multi-objective optimization problem is expressed with precisely selected three conflicting goals, incorporating reduction both loss deviation improvement A new index for called root mean square suggested. The proposed problems addressed using two freshly metaheuristic techniques optimal sitting sizing multiple SCs unity optimally factors RDS, presuming voltage-dependent load models. These thermal exchange (MOTEO) Lichtenberg algorithm (MOLA), which regarded as being physics-inspired techniques. MOLA inspired by physical phenomena lightning storms figures (LF), while MOTEO developed based on concept Newtonian cooling law. a hybrid differs from many literature since it combines population trajectory-based search approaches. Further, methodology implemented IEEE 69-bus network during scenarios, such bi- tri-objective problems. fetched simulation outcomes confirmed superiority achieving accurate non-dominated solutions fewer outliers standard among all studied metrics.

Language: Английский

Citations

18
SBOA: A Novel Heuristic Optimization Algorithm DOI Open Access
Qi Diao, Apri Junaidi, Weng Howe Chan

et al.

Baghdad Science Journal, Journal Year: 2024, Volume and Issue: 21(2(SI)), P. 0764 - 0764

Published: Feb. 25, 2024

تم تقديم طريقة تحسين إرشادية جديدة تعتمد على الإنسان، تسمى خوارزمية التحسين المستندة إلى السنوكر (SBOA)، في هذه الدراسة. الإلهام لهذه الطريقة مستوحى من سمات نخبة المبيعات - تلك الصفات التي يطمح كل مندوب مبيعات امتلاكها. عادةً ما يسعى مندوبو تعزيز مهاراتهم خلال التعلم الذاتي أو طلب التوجيه الآخرين. علاوة ذلك، فإنهم يشاركون اتصالات منتظمة مع العملاء للحصول الموافقة منتجاتهم خدماتهم. بناءً هذا المفهوم، تهدف SBOA إيجاد الحل الأمثل ضمن مساحة بحث معينة، واجتياز جميع المواضع القيم الممكنة. لتقييم جدوى وفعالية مقارنة بالخوارزميات الأخرى، أجرينا اختبارات عشر وظائف ذات هدف واحد الوظائف المعيارية لعام 2019 للحساب التطوري (CEC)، بالإضافة أربع وعشرين وظيفة CEC 2022. مرجعية، مشاكل هندسية. استخدام سبع خوارزميات مقارنة: التطور التفاضلي (DE)، العصفور (SSA)، جيب التمام (SCA)، الحيتان (WOA)، الفراشة (BOA)، سرب الأسد (LSO)، و ابن آوى الذهبي (GJO). وتمت نتائج التجارب المتنوعة حيث الدقة وسرعة منحنى التقارب. تشير النتائج أن هو نهج مباشر وقابل للتطبيق ويتفوق بشكل عام الخوارزميات المذكورة أعلاه.

Citations

7
Multiobjective Atomic Orbital Search (MOAOS) for Global and Engineering Design Optimization DOI Creative Commons
Mahdi Azizi, Siamak Talatahari, Nima Khodadadi

et al.

IEEE Access, Journal Year: 2022, Volume and Issue: 10, P. 67727 - 67746

Published: Jan. 1, 2022

In the real world, many optimization problems have such levels of uncertainty and complexity that a single objective function cannot represent all characteristics considered system. Hence, multi-objective algorithms are needed to account for multiple aspects problem, represented by functions, achieve reasonable useful results through procedure. this paper, we introduce version recently-developed single-objective metaheuristic algorithm known as Atomic Orbital Search (AOS), which will be called Multi-Objective (MOAOS). To end, general main searching loop AOS modified make it capable dealing with objectives. For performance evaluation algorithm, mathematical benchmark ZDT DTLZ, alongside several real-world engineering design CEC- 2020 MMO test problems, utilized. Based on obtained in study, can conclude MOAOS is producing either superior or closely comparable when evaluated competition alternative state-of-the-art methods.

Language: Английский

Citations

27
MOAEOSCA: an enhanced multi-objective hybrid artificial ecosystem-based optimization with sine cosine algorithm for feature selection in botnet detection in IoT DOI

Fatemeh Hosseini,

Farhad Soleimanian Gharehchopogh, Mohammad Masdari

et al.

Multimedia Tools and Applications, Journal Year: 2022, Volume and Issue: 82(9), P. 13369 - 13399

Published: Sept. 19, 2022

Language: Английский

Citations

26
Multi-objective structural optimization for the automatic member grouping of truss structures using evolutionary algorithms DOI
José Pedro Gonçalves Carvalho, Dênis E. C. Vargas, Breno Pinheiro Jacob

et al.

Computers & Structures, Journal Year: 2023, Volume and Issue: 292, P. 107230 - 107230

Published: Nov. 22, 2023

Language: Английский

Citations

13
Multi-objective Optimization of a Rectangular Microchannel Heat Sink Using Thermal Exchange Optimization Algorithm DOI
Lagouge K. Tartibu

Studies in computational intelligence, Journal Year: 2025, Volume and Issue: unknown, P. 239 - 270

Published: Jan. 1, 2025

Language: Английский

Citations

0