Genetic optimization of production line balancing

For example, five operators ( =5) are required to complete a production order. When skill inventory is 3, SI = 3, chromosome a = [2 1 3 1 1] implies that operator 1 shotrld process her second skilled task, operator 3 should process her third skilled task, and operators 2, 4 and 5 should process their first skilled tasks, respectively. Once skill levels, a, are defined, the operators responsible tasks and the corresponding operation efficiency are obtained fiom the predefined lookup table provided by the operative training department, as shown in Table 8.1. 

Initial population is generated randomly in this study. The initialization process is detailed as follows. 

In step 5 of the above procedure, the theoretical operative assignment is maintained in the initial population in order to speed up the optimization process. In the line balancing problem, the feasibility of each individual operative assignment is subject to various constraints. In the above routine, an individual is defined as a feasible solution in step 3 only when the following constraints are satisfied. 

fitness function is defined to measure the fitness of each individual chromosome so as to determine which will reproduce and survive into the next generation. Thus, given a particular chromosome, the fitness function returns a single numerical score, fitness , which is proportional to the ability of the individual that the chromosome represents. The fitness score assigned to each individual in the population depends on how well that individual solves a specific problem. In this line 

Single point crossover follows the procedures below. 

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