Milestone Methods, SOTA(Meta-Heuristics), Benchmark Problems

Thirty most used global optimization problems in the literature and best hybrid MHS Algorithms on Real World Optimization Problems

"New Hypotheses for designing meta-heuristic search algorithms (MHSs)", "Competitive SOTA Algorithms" and "Classic Test Problems Benchmark Suite"

A) Milestone methods in the design of meta-heuristic search algorithms (MHSs) and studies in which they are introduced

1) Fitness-distance balance (FDB) : "Guidance mechanism design method for MHSs"

• Kahraman, Hamdi Tolga; ARAS, Sefa; GEDIKLI, Eyüp. Fitness-distance balance (FDB): a new selection method for meta-heuristic search algorithms. Knowledge-Based Systems, 2020, 190: 105169.

https://se.mathworks.com/matlabcentral/fileexchange/72311-fdb-sos?s_tid=srchtitle

2) Natural Survivor Method (NSM) : "Update mechanism design method for MHSs"

• Kahraman, H. T., Katı, M., Aras, S., & Taşci, D. A. (2023). Development of the Natural Survivor Method (NSM) for designing an updating mechanism in metaheuristic search algorithms. Engineering Applications of Artificial Intelligence, 122, 106121.

https://se.mathworks.com/matlabcentral/fileexchange/126050-natural-survivor-method-nsm-for-metaheuristic-algorithms?s_tid=srchtitle

3) Fitness-Distance-Constraint (FDC) : "Guidance mechanism design method for MHSs"

• Ozkaya, B., Kahraman, H. T., Duman, S., & Guvenc, U. (2023). Fitness-Distance-Constraint (FDC) based guide selection method for constrained optimization problems. Applied Soft Computing, 110479.

https://se.mathworks.com/matlabcentral/fileexchange/130244-fitness-distance-constraint-in-constrained-optimization

4) dynamic Fitness-Distance Balance (dFDB) : "Guidance mechanism design method for MHSs"

• Kahraman, H. T., Bakir, H., Duman, S., Katı, M., Aras, S., & Guvenc, U. (2022). Dynamic FDB selection method and its application: modeling and optimizing of directional overcurrent relays coordination. Applied Intelligence, 52(5), 4873-4908.

https://se.mathworks.com/matlabcentral/fileexchange/96113-dfdb-mrfo-a-powerful-meta-heuristic-optimization-algorithm?s_tid=srchtitle

5) Adaptive fitness-distance balance (AFDB) : "Guidance mechanism design method for MHSs"

• Duman, S., Kahraman, H. T., & Kati, M. (2023). Economical operation of modern power grids incorporating uncertainties of renewable energy sources and load demand using the adaptive fitness-distance balance-based stochastic fractal search algorithm. Engineering Applications of Artificial Intelligence, 117, 105501.

https://se.mathworks.com/matlabcentral/fileexchange/118485-afdb-sfs?s_tid=ta_fx_results

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B) Milestone methods in the design of Multi-Objective Evolutionary Algorithms (MOEAs) and studies in which they are introduced

DRSC theorem: Dynamic Reference Spaces based Clustering (DRSC) as a new archive handling method

1) DRSC-MOAGDE

• Akbel, M., Kahraman, H. T., Duman, S., Temel, S. (2024). A clustering‑based archive handling method and multi‑objective optimization of the optimal power flow problem. Applied Intelligence, https://doi.org/10.1007/s10489-024-05714-5..

https://www.mathworks.com/matlabcentral/fileexchange/171434-drsc-moagde

https://link.springer.com/article/10.1007/s10489-024-05714-5

DSC theorem: Unified space approach-based Dynamic Switched Crowding (DSC): A new method for designing Pareto-based multi/many-objective algorithms

2) DSC-MOAGDE

• Kahraman, H. T., Akbel, M., Duman, S., Kati, M., & Sayan, H. H. (2022). Unified space approach-based Dynamic Switched Crowding (DSC): A new method for designing Pareto-based multi/many-objective algorithms. Swarm and Evolutionary Computation, 75, 101196.

https://www.mathworks.com/matlabcentral/fileexchange/119378-dynamic-switched-crowding-and-new-multiobjective-dsc-moagde?s_tid=ta_fx_results

3) DSC-MOSOS:

Combined heat and power economic emission dispatch using dynamic switched crowding based multi-objective symbiotic organism search algorithm

• Ozkaya, B., Kahraman, H. T., Duman, S., Guvenc, U., & Akbel, M. (2024). Combined heat and power economic emission dispatch using dynamic switched crowding based multi-objective symbiotic organism search algorithm. Applied Soft Computing, 151, 111106.

https://www.sciencedirect.com/science/article/pii/S1568494623011249?via%3Dihub

https://www.mathworks.com/matlabcentral/fileexchange/155697-dsc-mosos/?s_tid=LandingPageTabfx

4) DSC-MOPSO

• Bakir, H., Kahraman, H. T., Yilmaz, S., Duman, S., Guvenc, U. (2024). Dynamic Switched Crowding-based Multi-Objective Particle Swarm Optimization Algorithm for Solving Multi-Objective AC-DC Optimal Power Flow Problem. Applied Soft Computing, https://doi.org/10.1016/j.asoc.2024.112155.

https://www.mathworks.com/matlabcentral/fileexchange/171984-dsc-mopso?s_tid=ta_fx_results

https://www.sciencedirect.com/science/article/pii/S1568494624009293

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C)Links for source codes of the most up-to-date and competitive sigle objective SOTA algorithms in the literature:

Here are a few SOTA algorithms that demonstrate competitive search performance on classic single-objective optimization problems suites, IEEE CEC benchmark problems suites, and real-world constrained engineering optimization problems:

1) AFDB-ARO

• Ozkaya, B., Duman, S., Kahraman, H. T., & Guvenc, U. (2024). Optimal solution of the combined heat and power economic dispatch problem by adaptive fitness-distance balance based artificial rabbits optimization algorithm. Expert Systems with Applications, Volume 238, Part F, 122272.

https://se.mathworks.com/matlabcentral/fileexchange/136846-afdb-aro-an-improved-aro-algorithm-for-optimization-problem?s_tid=ta_fx_results

2) dFDB-SFS

• Kahraman, H. T., Hassan, M. H., Katı, M., Tostado-Véliz, M., Duman, S., & Kamel, S. (2023). Dynamic-fitness-distance-balance stochastic fractal search (dFDB-SFS algorithm): an effective metaheuristic for global optimization and accurate photovoltaic modeling. Soft Computing, 1-28.

https://www.mathworks.com/matlabcentral/fileexchange/156762-an-improved-stochastic-fractal-search-algorithm-dfdb-sfs

3) FDB-AGSK

• Bakır, H., Duman, S., Guvenc, U., & Kahraman, H. T. (2023). Improved adaptive gaining-sharing knowledge algorithm with FDB-based guiding mechanism for optimization of optimal reactive power flow problem. Electrical Engineering, 1-40.

https://se.mathworks.com/matlabcentral/fileexchange/129154-fdb-agsk?s_tid=srchtitle

4) FDB-TLABC

• Duman, S., Kahraman, H. T., Sonmez, Y., Guvenc, U., Kati, M., & Aras, S. (2022). A powerful meta-heuristic search algorithm for solving global optimization and real-world solar photovoltaic parameter estimation problems. Engineering Applications of Artificial Intelligence, 111, 104763.

https://se.mathworks.com/matlabcentral/fileexchange/106920-fdb-tlabc-a-powerful-meta-heuristic-optimization-algorithm?s_tid=srchtitle

5) FDB-AEO

• Sonmez, Y., Duman, S., Kahraman, H. T., Kati, M., Aras, S., & Guvenc, U. (2022). Fitness-distance balance based artificial ecosystem optimisation to solve transient stability constrained optimal power flow problem. Journal of Experimental & Theoretical Artificial Intelligence, 1-40.

https://se.mathworks.com/matlabcentral/fileexchange/115785-fdb-aeo?s_tid=srchtitle

6) FDB-LFD

• Bakir, H., Guvenc, U., Kahraman, H. T., & Duman, S. (2022). Improved Lévy flight distribution algorithm with FDB-based guiding mechanism for AVR system optimal design. Computers & Industrial Engineering, 168, 108032.

https://se.mathworks.com/matlabcentral/fileexchange/107090-fdb-lfd-improved-levy-flight-distribution-algorithm?s_tid=srchtitle

7) FDB-AGDE

• Guvenc, U., Duman, S., Kahraman, H. T., Aras, S., & Katı, M. (2021). Fitness–Distance Balance based adaptive guided differential evolution algorithm for security-constrained optimal power flow problem incorporating renewable energy sources. Applied Soft Computing, 108, 107421.

https://se.mathworks.com/matlabcentral/fileexchange/90601-fdb-agde?s_tid=srchtitle

8) LRFDB-COA

• Duman, S., Kahraman, H. T., Guvenc, U., & Aras, S. (2021). Development of a Lévy flight and FDB-based coyote optimization algorithm for global optimization and real-world ACOPF problems. Soft Computing, 25(8), 6577-6617.

https://se.mathworks.com/matlabcentral/fileexchange/87864-lrfdb-coa?s_tid=srchtitle

9) FDB-SFS

• Aras, S., Gedikli, E., & Kahraman, H. T. (2021). A novel stochastic fractal search algorithm with fitness-Distance balance for global numerical optimization. Swarm and Evolutionary Computation, 61, 100821.

https://se.mathworks.com/matlabcentral/fileexchange/84405-fdb-sfs?s_tid=srchtitle

10) FDB-CHOA

Bakir, H., Kahraman, H. T., Temel, S., Duman, S., Guvenc, U., & Sonmez, Y. (2023). Development of an FDB-Based Chimp Optimization Algorithm for Global Optimization and Determination of the Power System Stabilizer Parameters. In Smart Applications with Advanced Machine Learning and Human-Centred Problem Design (pp. 337-365). Cham: Springer International Publishing.

https://se.mathworks.com/matlabcentral/fileexchange/123680-fdb-choa-an-improved-fdb-chimp-optimization-algorithm?s_tid=srchtitle

11) FDB-PPSO

Duman, S., Kahraman, H. T., Korkmaz, B., Bakir, H., Guvenc, U., & Yilmaz, C. (2023). Improved Phasor Particle Swarm Optimization with Fitness Distance Balance for Optimal Power Flow Problem of Hybrid AC/DC Power Grids. In The International Conference on Artificial Intelligence and Applied Mathematics in Engineering (pp. 307-336). Springer, Cham.

https://se.mathworks.com/matlabcentral/fileexchange/122882-fdb-ppso-an-improved-pso-algorithm-for-optimization-problems?s_tid=srchtitle

12) dFDB-GBO

Taşci, D. A., Kahraman, H. T., Kati, M., & Yilmaz, C. (2023). Improved Gradient-Based Optimizer with Dynamic Fitness Distance Balance for Global Optimization Problems. In The International Conference on Artificial Intelligence and Applied Mathematics in Engineering (pp. 247-269). Springer, Cham.

https://se.mathworks.com/matlabcentral/fileexchange/122857-dynamic-fitness-distance-balance-gradient-based-optimizer?s_tid=srchtitle

13) FDB-AOA

Yenipinar, B., Şahin, A., Sönmez, Y., Yilmaz, C., & Kahraman, H. T. (2023). Design Optimization of Induction Motor with FDB-Based Archimedes Optimization Algorithm for High Power Fan and Pump Applications. In The International Conference on Artificial Intelligence and Applied Mathematics in Engineering (pp. 409-428).

https://se.mathworks.com/matlabcentral/fileexchange/123042-fdb-aoa-an-improved-archimedes-optimization-algorithm?s_tid=srchtitle

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D) A new Routing Algorithm and TSP-D Problem Codes

1) FDB-EA

• Yılmaz, C., Cengiz, E., & Kahraman, H. T. (2024). A new evolutionary optimization algorithm with hybrid guidance mechanism for truck-multi drone delivery system. Expert Systems with Applications, 245, 123115.

https://www.mathworks.com/matlabcentral/fileexchange/156906-fdb-ea-a-new-routing-algorithm-and-tsp-d-problem-codes?s_tid=srchtitle

E)Global Optimization Problems Classic Benchmark Suite:

Finally, a benchmarking package is presented in the appendix. This benchmark suite consists of the most commonly used test problems in the literature to test and verify the performance of metaheuristic search algorithms. This benchmark suite includes thirty test problems whose problem size can be changed dynamically. This benchmark suite was used to develop SOTA algorithms from the literature and compare their performance.