arrow
Return

E2: A basic optimization method using exploration-exploitation concept

delete2025-09-29
delete0
PRE
AI
A
Alireza Askarzadeh *
M
Mohammad Ali Alipour
DOI:10.1007/s00500-025-10861-zdelete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
In the literature, there are dozens of heuristic methods for optimization, each claiming to be superior to the other methods in terms of performance. Though many researchers express that they have invented novel algorithms by simulating a new natural or man-made phenomenon, critics believe that many algorithms are a special case of the previous well-known methods. Regardless of this issue, in general, an optimization method is efficient if it can establish a good balance between two basic concepts, namely exploration and exploitation. In fact, the optimization algorithms employ various ways to execute these concepts.The present study emphasizes that by simply implementing the primary principles of optimization, a difficult problem can be effectively solved, potentially eliminating the need to develop or apply a complicated search method. For this aim, this paper proposes a basic and simple optimization method based on the exploration–exploitation concept, named E2. Based on the simulation results, it is found that on average, the sinusoidal function is a promising method for exploitation. Over a set of engineering design problems, it is observed that the results found by E2 are comparable to those of other methods. When E2 is applied to a large set of unimodal and multimodal benchmark functions, the results are more promising than those of particle swarm optimization (PSO) and genetic algorithm (GA). Furthermore, over a case study from power system, E2 shows comparable convergence rate compared to PSO.
Keywords:
Engineering optimization
Optimization algorithm
Exploration–Exploitation method
Exploitation function

Journal

Soft Computing cover
Soft Computing
IF:
2.5
Papers:
1.0W
Citations:
2.1W

Organization

Cited Papers

Cited Papers

Metaheuristic Optimization
err2011-01-01
err0
errOAAI
errXin-She Yang
errShare
errSave
Grey Wolf Optimizer
err2014-03-01
err1.3W
PREAI
errMirjalili, Seyedali; Mirjalili, Seyed Mohammad; Lewis, Andrew
errShare
errSave
A Modified Slime Mould Algorithm for Global Optimization
err2021-11-24
err0
errOAAI
errAn-Di Tang; Shang-Qin Tang; Tong Han; Huan Zhou; Lei Xie
errShare
errSave
Battlefield Optimization Algorithm☆
err2025-03-01
err2
PREAI
errSetiawan, Dadang; Suyanto, Suyanto; Erfianto, Bayu
errShare
errSave
Komodo Mlipir Algorithm
err2022-01-01
err32
errOAAI
errSuyanto, Suyanto; Ariyanto, Alifya Aisyah; Ariyanto, Alifya Fatimah
errShare
errSave
Adaptation in Natural and Artificial Systems
err
IF0
err1992-04-29
err0
PREAI
errJohn H. Holland
errShare
errSave
researcher View more