## 4 Results  
The results of the experimental comparison between the proposed approach and the benchmark approaches described in Section Benchmarks based on the evaluation metrics described in Section Evaluation Metrics are reported in this section. The boxplots in Figures 3-5 report the distribution of the evaluation metrics computed by comparing the proposed approach with the Horacle approach, the Zero Exploration approach, and the Continuous Exploration approach, respectively, for the eight components investigated in the case study described in Section 3.2.1. The boxes in a plot represent the interquartile range, which spans from the first to the third quartile; a line inside the box represents the median of the considered values; and a triangle indicates the mean value. The whiskers extend from the edges of the box to the minimum and maximum values within 1.5 times the interquartile range from the first and third quartiles, respectively.  
According to Figure 3, the proposed approach resulted, on average, in an increase of 42% in the overall cost compared to a decision-maker with perfect knowledge of the future (Horacle approach). However, this difference resulted in variance in the interquartile range from a minimum increase of 7% to a maximum increase of 56% for half of the considered components. The higher average differences between the evaluation metrics are observed in the delivery and order emission costs.  
Specifically, the delivery cost produced by the proposed approach was, on average, 45% higher than that of the Horacle approach. Instead, an average increase of 15% was observed in the order emission cost. No significant differences in the purchasing cost were observed between the two approaches.  
Different results were obtained by comparing the proposed approach with the Zero Exploration approach.  
According to Figure 4, the proposed approach produced, on average, a decrease of 20% in terms of the overall cost compared to an approach that optimizes the order allocation decision without considering the benefit of sending orders to suppliers to acquire new data (Zero Exploration approach). This difference was observed to potentially vary between a minimum decrease of 6% to a maximum reduction of 31% for 50% of the considered components. In addition, when comparing the proposed approach with the Zero Exploration approach, the average increase of 10% in the order emission cost was effectively counterbalanced by an improved capability of reducing the delivery cost (by 21% on average). Also, in this comparison, the two approaches exhibited no significant difference in the purchasing cost.  
Lastly, the results of the comparison between the proposed approach and the Continuous Exploration approach are reported in Figure 5.  
Similarly to the previous comparison, Figure 5 highlights an advantage of the proposed approach over the Continuous Exploration approach in solving the multiperiod SSOA problem, corresponding on average to a decrease of 21% in the overall cost. The average decrease of 38% in order emission costs did not lead the proposed approach to produce higher delivery costs. Indeed, the delivery cost reported by the proposed approach was 20% lower on average than the one reported for the benchmark approach. Also, no significant differences in purchasing cost were seen between the two approaches.