A comparative evaluation of heuristic line balancing techniques
Management Science
A survey of exact algorithms for the simple assembly line balancing problem
Management Science
Optimally balancing large assembly lines with `FABLE'
Management Science
Two-sided assembly line balancing to maximize work relatedness and slackness
Computers and Industrial Engineering
A symbiotic evolutionary algorithm for the integration of process planning and job shop scheduling
Computers and Operations Research
Multileveled Symbiotic Evolutionary Algorithm: Application to FMS Loading Problems
Applied Intelligence
Computers and Operations Research
Balancing of mixed-model two-sided assembly lines
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
Bee colony intelligence in zone constrained two-sided assembly line balancing problem
Expert Systems with Applications: An International Journal
Computers and Industrial Engineering
Rule-based modeling and constraint programming based solution of the assembly line balancing problem
Expert Systems with Applications: An International Journal
Computers and Industrial Engineering
Reduction approaches for a generalized line balancing problem
Computers and Operations Research
Computers and Industrial Engineering
Two-sided assembly line balancing considering the relationships between tasks
Computers and Industrial Engineering
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A two-sided assembly line is a type of production line where tasks are performed in parallel at both sides of the line. The line is often found in producing large products such as trucks and buses. This paper presents a mathematical model and a genetic algorithm (GA) for two-sided assembly line balancing (two-ALB). The mathematical model can be used as a foundation for further practical development in the design of two-sided assembly lines. In the GA, we adopt the strategy of localized evolution and steady-state reproduction to promote population diversity and search efficiency. When designing the GA components, including encoding and decoding schemes, procedures of forming the initial population, and genetic operators, we take account of the features specific to two-ALB. Through computational experiments, the performance of the proposed GA is compared with that of a heuristic and an existing GA with various problem instances. The experimental results show that the proposed GA outperforms the heuristic and the compared GA.