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Session:

Late Breaking Paper

Title:

Variable Neighborhood Particle Swarm Optimization Algorithm

 

 

Authors:

Ajith Abraham
Hongbo Liu
Tae-Gyu Chang

 

 

Abstract:

In this paper, we introduce a hybrid metaheuristic, the Variable Neighborhood Particle Swarm Optimization (VNPSO) algorithm, consisting of a combination of the Variable Neighborhood Search (VNS) and Particle Swarm Optimization(PSO). The proposed VNPSO algorithm is used for solving the multi-objective Flexible Job-shop Scheduling Problems (FJSP). Flexible job-shop scheduling is very important in both fields of production management and combinatorial optimization. However, it is quite difficult to achieve an optimal solution with traditional optimization approaches owing to the high computational complexity. The details of implementation for the multi-objective FJSP are provided and the corresponding computational experiments are reported. The results indicate that the proposed algorithm is an efficient approach for the multi-objective FJSP, especially for large scale problems.

 

 

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