Title : 
Mixed-Model Assembly Line Balancing Based on PSO-SA Alternate Algorithm
         
        
        
            Author_Institution : 
Transp. Manage. Sch., Zhejiang Inst. of Commun., Hangzhou, China
         
        
        
        
        
        
        
            Abstract : 
According to the characteristic of the mixed-model assembly line balancing problem, the multi-objective optimization mathematical model is set up, PSO-SA alternate algorithm which is based on is Particle Swarm Optimization Algorithm and Simulated Annealing Algorithm is proposed to solve the MMALB problem. The result shows that the PSO-SA algorithm is better efficient on the search speed and solution accuracy, which ensures a higher assembly line balancing ratio and makes the work time more even among all stations. The PSO-SA algorithm for the mixed-model assembly line balancing is feasible and effective.
         
        
            Keywords : 
assembling; particle swarm optimisation; simulated annealing; MMALB problem; PSO-SA alternate algorithm; mixed model assembly line balancing; particle swarm optimization; simulated annealing algorithm; Assembly; Automation; Conference management; Genetic algorithms; Mathematical model; Particle swarm optimization; Production; Simulated annealing; Stochastic processes; Sun; PSO-SA alternate algorithm; balancing efficiency; encode and decode; mixed-model assembly line balancing; smoothing exponential;
         
        
        
        
            Conference_Titel : 
Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
         
        
            Conference_Location : 
Changsha
         
        
            Print_ISBN : 
978-1-4244-7279-6
         
        
            Electronic_ISBN : 
978-1-4244-7280-2
         
        
        
            DOI : 
10.1109/ICICTA.2010.9