PURPOSES : The objective of this study is to evaluate the feasibility of applying properties of asphalt binder other than absolute viscosity (AV) to evaluate the rejuvenation level of the binder from reclaimed asphalt pavement (RAP) in recycled asphalt mixtures (RAMs). METHODS : The G*/sin and critical temperature (CT) for determining high performance grade by DSR, and the large molecular size (LMS) using gel-permeation chromatography (GPC) were measured simultaneously with the AV of two virgin asphalt binders (58–22 for RAM and 64–22 for normal mix) and recovered binders from a RAP and four RAMs. Based on mix design, 20%, 30%, 40%, and 50% recycled RAMs were prepared, and the deformation strength (SD) of the RAMs were measured. The AV, LMS, G*/sin , and CT were measured from the recovered binders from each RAM of the SD-tested specimens. Regression analyses were performed between the LMS and AV, G*/ sin and AV, and CT and AV to determine the correlation of each property with the AV. The feasibility of evaluating the rejuvenation level of the RMA binder using the three properties (LMS, G*/sin , and CT) was evaluated. Regression analysis was performed between SD and AV, and the feasibility of using SD instead of AV ≤ 5,000 poise (p) was analyzed to evaluate the rejuvenation level of the RAM. RESULTS : The AV, LMS, G*/sin , and CT of RAM binders increased with the recycling ratio. Mixes with recycle ratios of 20% and 30% satisfied the AV ≤ 5,000 p criterion, unlike mixes with higher recycle ratios. The regression analysis results showed that the R2 values between the LMS and AV, G*/sin and AV, and CT and AV exceeded 0.96. Since these regressions showed extremely high R2 values, it can be inferred that the estimation of binder rejuvenation level using the LMS, G*/sin and CT, i.e., instead of the AV criterion, is applicable. Because SD exhibits high correlation with the binder stiffness, and the regression between SD and AV indicated R2 > 0.98, SD can be applied instead of the AV for binder rejuvenation level estimation. The main advantage of using the LMS and SD is to estimate the binder rejuvenation level without recovering the binder from the mix. CONCLUSIONS : For the binder rejuvenation level estimation of recycled mixes, it is concluded that the LMS by GPC and G*/sin and CT by DSR, and SD can be applied instead of the AV criterion. However, since this study was performed using limited materials, further studies involving many other materials may be performed to generalize the current conclusion.

Aggregate Production Planning determines levels of production, human resources, inventory to maximize company’s profits and fulfill customer's demands based on demand forecasts. Since performance of aggregate production planning heavily depends on accuracy of given forecasting demands, choosing an accurate forecasting method should be antecedent for achieving a good aggregate production planning. Generally, typical forecasting error metrics such as MSE (Mean Squared Error), MAD (Mean Absolute Deviation), MAPE (Mean Absolute Percentage Error), and CFE (Cumulated Forecast Error) are utilized to choose a proper forecasting method for an aggregate production planning. However, these metrics are designed only to measure a difference between real and forecast demands and they are not able to consider any results such as increasing cost or decreasing profit caused by forecasting error. Consequently, the traditional metrics fail to give enough explanation to select a good forecasting method in aggregate production planning. To overcome this limitation of typical metrics for forecasting method this study suggests a new metric, WACFE (Weighted Absolute and Cumulative Forecast Error), to evaluate forecasting methods. Basically, the WACFE is designed to consider not only forecasting errors but also costs which the errors might cause in for Aggregate Production Planning. The WACFE is a product sum of cumulative forecasting error and weight factors for backorder and inventory costs. We demonstrate the effectiveness of the proposed metric by conducting intensive experiments with demand data sets from M3-competition. Finally, we showed that the WACFE provides a higher correlation with the total cost than other metrics and, consequently, is a better performance in selection of forecasting methods for aggregate production planning.