Pareto process optimization of product development project using bi-objective hybrid genetic algorithm

A Pareto supplier selection algorithm for minimum the life cycle cost of complex product system

“…The individual assigned the smaller rank value, represents it is the better one. Furthermore, map the rank value to fitness value with the following formula for normalization modified from (Che and Chiang 2010;Wang et al 2013). …”

“…The stochastic tournament strategy (Lei 2011) and elite preservation strategy (Wang et al 2013) are applied in this study to selection operator. The stochastic tournament strategy is implemented on the whole individuals and randomly chosen a series of individuals and retained the highest fitness individual to next generation, while elite preservation strategy is implemented on the global optimal individuals to replace the worst individuals in next generation.…”

“…Improving one objective will compromise another. For bi-objective optimization problem, it is desirable for Pareto optimal values to be evenly distributed in Pareto-optimal solution set, rather than converged in a single region of Pareto front (Wang et al 2013). …”

A Production Planning Model for Make-to-Order Foundry Flow Shop with Capacity Constraint

“…Selection Operator. The stochastic tournament strategy [52][53][54] and elite preservation strategy [55][56][57] are adopted in this paper of selection operator. The stochastic tournament strategy is implemented on the whole individuals, randomly chose a series of individuals, and retained the individual which has highest fitness to next generation.…”