>
Fa   |   Ar   |   En
   A multi-objective genetic algorithm for a mixed-model assembly U-line balancing type-I problem considering human-related issues, training, and learning  
   
نویسنده Rabbani Masoud ,Montazeri Mona ,Farrokhi-Asl Hamed ,Rafiei Hamed
منبع journal of industrial engineering international - 2016 - دوره : 12 - شماره : 4 - صفحه:485 -497
چکیده    Mixed-model assembly lines are increasingly accepted in many industrial environments to meet the growing trend of greater product variability, diversification of customer demands, and shorter life cycles. in this research, a new mathematical model is presented considering balancing a mixed-model u-line and human-related issues, simultaneously. the objective function consists of two separate components. the first part of the objective function is related to balance problem. in this part, objective functions are minimizing the cycle time, minimizing the number of workstations, and maximizing the line efficiencies. the second part is related to human issues and consists of hiring cost, firing cost, training cost, and salary. to solve the presented model, two well-known multi-objective evolutionary algorithms, namely non-dominated sorting genetic algorithm and multi-objective particle swarm optimization, have been used. a simple solution representation is provided in this paper to encode the solutions. finally, the computational results are compared and analyzed.
کلیدواژه Mixed-model assembly lines  U-shapedassembly lines ,Learning and training effect ,Human-related issues ,Multi-objective
آدرس university of tehran, School of Industrial Engineering, College of Engineering, ایران, university of tehran, School of Industrial Engineering, College of Engineering, ایران, iran university of science and technology, School of Industrial Engineering, ایران, university of tehran, School of Industrial Engineering, College of Engineering, ایران
 
     
   
Authors
  
 
 

Copyright 2023
Islamic World Science Citation Center
All Rights Reserved