PERSONALIZED SPORTS TRAINING PLANS WITH PHYSIOLOGICAL CONSTRAINTS USING THE ε-CONSTRAINT METHOD WITH A GENETIC ALGORITHM

摘要

A personalized sports training plan specifies a personalized schedule of performance training that will achieve optimization of the athlete's performance. The genetic algorithm (GA) is a well known method that could be applied to optimize the effectiveness of a training plan, but such a training plan would still be subject to certain constraints that can limit its effectiveness. Exclusion of physiological constraints; training monotony, chronic training load ramp rate (CTLRampRate), and daily training load are important examples. To overcome these shortcomings, and to ensure the effectiveness of a training plan, the s-constraint method was applied to modify the GA to recognize and acknowledge these constraints thereby enhancing the effectiveness of the training plan. The results show that an optimized sports training plan can be achieved by applying the GA, modified by the ε-constraint method, with the ultimate outcome of attaining heightened athletic performance.