Hybrid improved sine cosine algorithm for mixed-integer nonlinear programming problems

Aiming at the shortcomings of existing algorithms in solving mixed-integer programming problems, such as local convergence and poor solution accuracy, this paper presents a hybrid improved sine and cosine algorithm. The improved position update formula is introduced to enhance the global and local s...

Full description

Saved in:
Bibliographic Details
Published in:Soft computing (Berlin, Germany) Vol. 27; no. 20; pp. 14909 - 14933
Main Authors: Song, Haohao, Wang, Jiquan, Cheng, Zhiwen, Chang, Tiezhu
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2023
Springer Nature B.V
Subjects:
ISSN:1432-7643, 1433-7479
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Aiming at the shortcomings of existing algorithms in solving mixed-integer programming problems, such as local convergence and poor solution accuracy, this paper presents a hybrid improved sine and cosine algorithm. The improved position update formula is introduced to enhance the global and local search abilities of the algorithm, and combined mutation is further given to avoid local convergence. The performance of proposed algorithm is validated by the high-dimensional modified CEC 2017 COPs and two complex engineering optimization problems. The experimental findings indicate that the hybrid mechanism of improved sine and cosine algorithm and combined mutation is demonstrably effective, and the proposed algorithm provides a satisfactory solution for addressing high-dimensional complicated mixed-integer programming problems.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1432-7643
1433-7479
DOI:10.1007/s00500-023-08578-y