An Enhanced Five Phases Algorithm Based on Fitness-Distance Balance Selection

Xiaopeng Wang; V. Snášel; S. Mirjalili; S.-C. Chu; Rizk M. Rizk-Allah

doi:10.1007/978-981-96-4434-6_24

An Enhanced Five Phases Algorithm Based on Fitness-Distance Balance Selection

Xiaopeng Wang
, V. Snášel
, S. Mirjalili
, S.-C. Chu
, Rizk M. Rizk-Allah

Business and Hospitality

Research output: Contribution to conference › Paper › peer-review

Abstract

Five phases algorithm (FPA) is one of the most effective algorithms for solving global optimization problems. The search operations consist of generating and overcoming strategy, and learning strategy. The algorithm has a simple structure and no predefined parameters, providing flexibility for practitioners. This paper suggests an enhanced form of FPA, named eFPA. The purpose is to prevent the algorithm from getting stuck in local optima and premature convergence in complex problems. We combine the fitness-distance balance method to redesign the generating and overcoming strategy. The designed algorithm is tested using the CEC 2022 and compared with the nine advanced algorithms. The statistical test results show that the proposed eFPA is highly competitive and explores the search space better than the compared algorithms. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.

Original language	English
Pages	281-292
Number of pages	12
DOIs	https://doi.org/10.1007/978-981-96-4434-6_24
Publication status	Published - 2026
Event	20th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2024 is held in conjunction with the 19th International Symposium on Management Engineering, ISME 2024 - Matsue, Japan Duration: 4 Oct 2024 → 6 Oct 2024 Conference number: 343629

Conference

Conference	20th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2024 is held in conjunction with the 19th International Symposium on Management Engineering, ISME 2024
Country/Territory	Japan
City	Matsue
Period	4/10/24 → 6/10/24

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being
SDG 7 Affordable and Clean Energy
SDG 9 Industry, Innovation, and Infrastructure
SDG 11 Sustainable Cities and Communities
SDG 12 Responsible Consumption and Production
SDG 13 Climate Action
SDG 17 Partnerships for the Goals

Keywords

Evolutionary computation
Fitness-distance balance
Five phases algorithm
Global optimization
Metaheuristic algorithm
Evolutionary algorithms
Problem solving
Shape optimization
Algorithm for solving
Distance balance
Effective algorithms
Five phase algorithm
Five-phase
Global optimisation
Global optimization problems
Meta-heuristics algorithms
Search operations

Access to Document

10.1007/978-981-96-4434-6_24

https://www.scopus.com/inward/record.uri?eid=2-s2.0-105022977417&doi=10.1007%2f978-981-96-4434-6_24&partnerID=40&md5=f77da39d028600008c1418aadb9e39aa

Cite this

Wang, X., Snášel, V., Mirjalili, S., Chu, S.-C., & Rizk-Allah, R. M. (2026). An Enhanced Five Phases Algorithm Based on Fitness-Distance Balance Selection. 281-292. Paper presented at 20th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2024 is held in conjunction with the 19th International Symposium on Management Engineering, ISME 2024, Matsue, Japan. https://doi.org/10.1007/978-981-96-4434-6_24

Wang, Xiaopeng ; Snášel, V. ; Mirjalili, S. et al. / An Enhanced Five Phases Algorithm Based on Fitness-Distance Balance Selection. Paper presented at 20th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2024 is held in conjunction with the 19th International Symposium on Management Engineering, ISME 2024, Matsue, Japan.12 p.

@conference{d9f94c589b3d4addaa1e114f9c1442a0,

title = "An Enhanced Five Phases Algorithm Based on Fitness-Distance Balance Selection",

abstract = "Five phases algorithm (FPA) is one of the most effective algorithms for solving global optimization problems. The search operations consist of generating and overcoming strategy, and learning strategy. The algorithm has a simple structure and no predefined parameters, providing flexibility for practitioners. This paper suggests an enhanced form of FPA, named eFPA. The purpose is to prevent the algorithm from getting stuck in local optima and premature convergence in complex problems. We combine the fitness-distance balance method to redesign the generating and overcoming strategy. The designed algorithm is tested using the CEC 2022 and compared with the nine advanced algorithms. The statistical test results show that the proposed eFPA is highly competitive and explores the search space better than the compared algorithms. {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.",

keywords = "Evolutionary computation, Fitness-distance balance, Five phases algorithm, Global optimization, Metaheuristic algorithm, Evolutionary algorithms, Problem solving, Shape optimization, Algorithm for solving, Distance balance, Effective algorithms, Five phase algorithm, Five-phase, Global optimisation, Global optimization problems, Meta-heuristics algorithms, Search operations",

author = "Xiaopeng Wang and V. Sn{\'a}{\v s}el and S. Mirjalili and S.-C. Chu and Rizk-Allah, \{Rizk M.\}",

note = "Export Date: 29 April 2026; Cited By: 0; Correspondence Address: V. Sn{\'a}{\v s}el; Faculty of Electrical Engineering and Computer Science, V{\v S}B-Technical University of Ostrava, Ostrava, Czech Republic; email: [email protected]; Conference name: 20th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2024 is held in conjunction with the 19th International Symposium on Management Engineering, ISME 2024; Conference date: 4 October 2024 through 6 October 2024; Conference code: 343629; 20th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2024 is held in conjunction with the 19th International Symposium on Management Engineering, ISME 2024 ; Conference date: 04-10-2024 Through 06-10-2024",

year = "2026",

doi = "10.1007/978-981-96-4434-6\_24",

language = "English",

pages = "281--292",

}

Wang, X, Snášel, V, Mirjalili, S, Chu, S-C & Rizk-Allah, RM 2026, 'An Enhanced Five Phases Algorithm Based on Fitness-Distance Balance Selection', Paper presented at 20th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2024 is held in conjunction with the 19th International Symposium on Management Engineering, ISME 2024, Matsue, Japan, 4/10/24 - 6/10/24 pp. 281-292. https://doi.org/10.1007/978-981-96-4434-6_24

An Enhanced Five Phases Algorithm Based on Fitness-Distance Balance Selection. / Wang, Xiaopeng; Snášel, V.; Mirjalili, S. et al.
2026. 281-292 Paper presented at 20th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2024 is held in conjunction with the 19th International Symposium on Management Engineering, ISME 2024, Matsue, Japan.

Research output: Contribution to conference › Paper › peer-review

TY - CONF

T1 - An Enhanced Five Phases Algorithm Based on Fitness-Distance Balance Selection

AU - Wang, Xiaopeng

AU - Snášel, V.

AU - Mirjalili, S.

AU - Chu, S.-C.

AU - Rizk-Allah, Rizk M.

N1 - Conference code: 343629

PY - 2026

Y1 - 2026

N2 - Five phases algorithm (FPA) is one of the most effective algorithms for solving global optimization problems. The search operations consist of generating and overcoming strategy, and learning strategy. The algorithm has a simple structure and no predefined parameters, providing flexibility for practitioners. This paper suggests an enhanced form of FPA, named eFPA. The purpose is to prevent the algorithm from getting stuck in local optima and premature convergence in complex problems. We combine the fitness-distance balance method to redesign the generating and overcoming strategy. The designed algorithm is tested using the CEC 2022 and compared with the nine advanced algorithms. The statistical test results show that the proposed eFPA is highly competitive and explores the search space better than the compared algorithms. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.

AB - Five phases algorithm (FPA) is one of the most effective algorithms for solving global optimization problems. The search operations consist of generating and overcoming strategy, and learning strategy. The algorithm has a simple structure and no predefined parameters, providing flexibility for practitioners. This paper suggests an enhanced form of FPA, named eFPA. The purpose is to prevent the algorithm from getting stuck in local optima and premature convergence in complex problems. We combine the fitness-distance balance method to redesign the generating and overcoming strategy. The designed algorithm is tested using the CEC 2022 and compared with the nine advanced algorithms. The statistical test results show that the proposed eFPA is highly competitive and explores the search space better than the compared algorithms. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.

KW - Evolutionary computation

KW - Fitness-distance balance

KW - Five phases algorithm

KW - Global optimization

KW - Metaheuristic algorithm

KW - Evolutionary algorithms

KW - Problem solving

KW - Shape optimization

KW - Algorithm for solving

KW - Distance balance

KW - Effective algorithms

KW - Five phase algorithm

KW - Five-phase

KW - Global optimisation

KW - Global optimization problems

KW - Meta-heuristics algorithms

KW - Search operations

U2 - 10.1007/978-981-96-4434-6_24

DO - 10.1007/978-981-96-4434-6_24

M3 - Paper

SP - 281

EP - 292

T2 - 20th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2024 is held in conjunction with the 19th International Symposium on Management Engineering, ISME 2024

Y2 - 4 October 2024 through 6 October 2024

ER -

Wang X, Snášel V, Mirjalili S, Chu SC, Rizk-Allah RM. An Enhanced Five Phases Algorithm Based on Fitness-Distance Balance Selection. 2026. Paper presented at 20th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2024 is held in conjunction with the 19th International Symposium on Management Engineering, ISME 2024, Matsue, Japan. doi: 10.1007/978-981-96-4434-6_24

An Enhanced Five Phases Algorithm Based on Fitness-Distance Balance Selection

Abstract

Conference

UN SDGs

Keywords

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