Home Research Papers Datasets State of the Art Pricing

Discover, visualize, and connect AI research papers. Explore the latest trends and insights in artificial intelligence research.

Product

Home
Research Papers
About

Support

Contact
Terms of Service
Privacy Policy

© 2026 Papersgraph. All rights reserved.

methodology-6

Metaheuristic Optimization

3260 papers • 126 benchmarks • 313 datasets

In computer science and mathematical optimization, a metaheuristic is a higher-level procedure or heuristic designed to find, generate, or select a heuristic (partial search algorithm) that may provide a sufficiently good solution to an optimization problem. For some examples, you can visit https://aliasgharheidari.com/Publications.html

(Image credit: Papersgraph)

Benchmarks

These leaderboards are used to track progress in metaheuristic-optimization-6

Trend

Dataset

Best Model

Actions

No benchmarks available.

Libraries

i

Use these libraries to find metaheuristic-optimization-6 models and implementations

Datasets

OSTD

Subtasks

No subtasks available.

Most implemented papers

Donkey and Smuggler Optimization Algorithm: A Collaborative Working Approach to Path Finding

Ahmed S. Shamsaldin, R. Agha, Nawzad K. Al-Salihi, M. Mohammadi•Thu Apr 18 2019

A novel algorithm called Donkey and Smuggler Optimization Algorithm (DSO), inspired by the searching behavior of donkeys, which is adapted and implemented on three real-world applications namely; traveling salesman problem, packet routing, and ambulance routing.

83

Content

Introduction Benchmarks Datasets Subtasks Libraries Papers

0

Gnowee: A Hybrid Metaheuristic Optimization Algorithm for Constrained, Black Box, Combinatorial Mixed-Integer Design

J. Bevins, R. Slaybaugh•Sat Apr 14 2018

This paper introduces Gnowee, a modular, Python-based, open-source hybrid metaheuristic optimization algorithm designed for rapid convergence to nearly globally optimum solutions for complex, constrained nuclear engineering problems with mixed-integer and combinatorial design vectors and high-cost, noisy, discontinuous, black box objective function evaluations.

7 0

Pontogammarus Maeoticus Swarm Optimization: A Metaheuristic Optimization Algorithm

Benyamin Ghojogh, Saeed Sharifian•Wed Jul 04 2018

Pontogammarus Maeoticus Swarm Optimization (PMSO) is a metaheuristic algorithm imitating aquatic nature and foraging behavior modeled as sea edge (coast) to which Gammarus creatures are willing to move in order to rest from sea waves and forage in sand.

1 0

Tree-Based Optimization: A Meta-Algorithm for Metaheuristic Optimization

H. Mohammadzade, Benyamin Ghojogh, Saeed Sharifian•Mon Sep 24 2018

A meta-algorithm, Tree-Based Optimization (TBO), which uses other heuristic optimizers as its sub-algorithms in order to improve the performance of search and improve the speed of search.

7 0

Multi-modal forest optimization algorithm

M. Feizi-Derakhshi, Mohanna Orujpour, Taymaz Rahkar-Farshi•Mon Mar 04 2019

The experiment results show that not only is the population size low, but also that the convergence speed is high, and that the algorithm is efficient in solving multi-modal problems.

24 0

ILS-SUMM: Iterated Local Search for Unsupervised Video Summarization

Yair Shemer, Daniel Rotman, N. Shimkin•Tue Sep 24 2019

ILS-SUMM is developed, a novel video summarization algorithm to solve the subset selection problem under the knapsack constraint based on the well-known metaheuristic optimization framework Iterated Local Search (ILS), known for its ability to avoid weak local minima and obtain a good near-global minimum.

15 0

Battle royale optimization algorithm

Taymaz Rahkar Farshi•Mon Jun 01 2020

The experimental results show that the proposed novel metaheuristic optimization algorithm, named BRO (battle royale optimization), is an efficient method and provides promising and competitive results.

199 0

Motion-Encoded Particle Swarm Optimization for Moving Target Search Using UAVs

Q. Ha, Manh Duong Phung•Wed Sep 09 2020

The proposed MPSO improves the detection performance by 24% and time performance by 4.71 times compared to the original PSO, and also outperforms other state-of-the-art metaheuristic optimization algorithms including the artificial bee colony (ABC), ant colony optimization (ACO), genetic algorithm (GA), differential evolution (DE), and tree-seed algorithm (TSA) in most search scenarios.

90 0

Safety-enhanced UAV Path Planning with Spherical Vector-based Particle Swarm Optimization

Q. Ha, Manh Duong Phung•Mon Apr 12 2021

The results show that the proposed SPSO outperforms not only other particle swarm optimization (PSO) variants including the classic PSO, phase angle-encoded PSO and quantum-behave PSO but also other state-of-the-art metaheuristic optimization algorithms including the genetic algorithm (GA), artificial bee colony (ABC), and differential evolution (DE) in most scenarios.

431 0

Adding a benchmark result helps the community track progress.

Metaheuristic Optimization | State-of-the-Art