Open AccessA New Hybrid Meta-Heuristics Algorithms to Solve APP Problems
Author(s) -
Bayda Atiya Kalaf,
Ghadeer Jasim Mohammed,
Muna D. Salman
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 - 10.1088/1742-6596/1897/1/012011
Subject(s) - hybrid algorithm (constraint satisfaction) , particle swarm optimization , simulated annealing , computer science , mathematical optimization , heuristics , algorithm , linear programming , mathematics , constraint programming , stochastic programming , constraint logic programming
In this paper, a new hybrid algorithm for linear programming model based on Aggregate production planning problems is proposed. The new hybrid algorithm of a simulated annealing (SA) and particle swarm optimization (PSO) algorithms. PSO algorithm employed for a good balance between exploration and exploitation in SA in order to be effective and efficient (speed and quality) for solving linear programming model. Finding results show that the proposed approach is achieving within a reasonable computational time comparing with PSO and SA algorithms.