Performance comparison of genetic algorithms and particle swarm optimization for model integer programming bus timetabling problem

Indonesian Operations Research Association - International Conference on Operations Research 2017

Wihartiko, F.D.^1 ; Wijayanti, H.^2 ; Virgantari, F.^2

Departement of Computer Science, Pakuan University, Indonesia^1

Departement of Mathematic, Pakuan University, Indonesia^2

关键词: Bus timetabling;    Comparison result;    Optimal number;    Optimal solutions;    Optimization problems;    Particle swarm optimization algorithm;    Performance comparison;    PSO algorithms;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/332/1/012020/pdf
DOI  :  10.1088/1757-899X/332/1/012020

来源: IOP

【 摘 要 】

Genetic Algorithm (GA) is a common algorithm used to solve optimization problems with artificial intelligence approach. Similarly, the Particle Swarm Optimization (PSO) algorithm. Both algorithms have different advantages and disadvantages when applied to the case of optimization of the Model Integer Programming for Bus Timetabling Problem (MIPBTP), where in the case of MIPBTP will be found the optimal number of trips confronted with various constraints. The comparison results show that the PSO algorithm is superior in terms of complexity, accuracy, iteration and program simplicity in finding the optimal solution.