A survey of exact algorithms for the simple assembly line balancing problem
Management Science
Binary integer formulation for mixed-model assembly line balancing problem
Computers and Industrial Engineering
Two-sided assembly line balancing to maximize work relatedness and slackness
Computers and Industrial Engineering
A new heuristic method for mixed model assembly line balancing problem
Computers and Industrial Engineering
A mathematical model and a genetic algorithm for two-sided assembly line balancing
Computers and Operations Research
A genetic algorithm based approach to the mixed-model assembly line balancing problem of type II
Computers and Industrial Engineering
Balancing fuzzy multi-objective two-sided assembly lines via Bees Algorithm
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - FUZZYSS’2009
Computers and Industrial Engineering
Engineering Applications of Artificial Intelligence
Bee colony intelligence in zone constrained two-sided assembly line balancing problem
Expert Systems with Applications: An International Journal
A solution procedure for type E simple assembly line balancing problem
Computers and Industrial Engineering
Computers and Industrial Engineering
Enhanced mixed integer programming model for a transfer line design problem
Computers and Industrial Engineering
Assembly line balancing under uncertainty: Robust optimization models and exact solution method
Computers and Industrial Engineering
Two-sided assembly line balancing considering the relationships between tasks
Computers and Industrial Engineering
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This paper presents a new mathematical model and a simulated annealing algorithm for the mixed-model two-sided assembly line balancing problem. The proposed mathematical model minimizes the number of mated-stations (i.e., the line length) as the primary objective and minimizes the number of stations (i.e., the number of operators) as a secondary objective for a given cycle time. In the proposed simulated annealing algorithm, two performance criteria are considered simultaneously: maximizing the weighted line efficiency and minimizing the weighted smoothness index. The proposed approach is illustrated with an example problem, and its performance is tested on a set of test problems. The experimental results show that the proposed approach performs well.