Open AccessAn improved sine cosine algorithm for assignment problem
Author(s) -
Dan Ye,
Yu Liu,
Shan Zhang,
Fei Yu,
Hongyu Meng,
Bo Li,
Erzhen Shang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2031/1/012057
Subject(s) - sine , particle swarm optimization , trigonometric functions , mathematical optimization , algorithm , local optimum , chaotic , greedy algorithm , discrete cosine transform , computer science , optimization problem , differential evolution , mathematics , artificial intelligence , geometry , image (mathematics)
The assignment problem is a NP-hard combinatorial optimization problem, where assignees are being assigned to perform tasks. This paper presents an improved sine and cosine algorithm (ISCA) to solve this problem. Nonlinear decreasing inertia weight, chaotic map and greedy strategy are added to the original sine cosine algorithm (SCA) to enhance the ability of focusing on optimal and avoiding local optima. Simulation results show that the proposed algorithm can get more competitive solutions when compared with differential evolution (DE), particle swarm optimization (PSO) and original SCA.