The depletion of natural aggregate sources which generally accounts for a huge percent of Hot Mixed Asphalts (HMAs) and the difficulty posed by disposal scrap tires are a major environmental concern for the future. The use of waste products like scrap tires in highway construction is considered a sustainable way of dealing with these issues. Crumb rubber is a material pulverized from waste polymer products like scrap tires which are then added to HMAs to improve their performance. This study focuses on the sensitivity of crumb rubber particle sizes (fine ≤1.18 mm), (coarse ≥1.18 mm and ≤3.35 mm) (and mix of 50% fine and 50% coarse) and partial replacement (1.5 and 2.5% of total weight) of aggregates on the Marshall test parameters of rubberized asphalt mixes. The Marshall test parameters: density, stability, VTM, VFB of both rubberized asphalt and conventional asphalt samples were compared and also the Asphalt Institute (AI) and National Asphalt Pavement Association (NAPA) methods were used to obtain the optimum bitumen content (OBC). From the results, it suggests that; the utilization of dry process methodology of adding crumb rubber additives in different sizes and percentages had a considerable effect on Marshal test parameters and also influences the optimum binder content estimates. The results of this study can be used as a reference point for the use of crumb rubber in HMAs.

A sustainable urban transportation system uses different classes of transportation modes whose services should be well integrated. The Feeder Bus Route Network Problem (FBRNDP) is an important part of this integration. FBRNDP primarily deals with the provision of access to an existing mainline movement through feeder transit system usually to expand it's the service coverage. The multiple traveling salesman problem (MTSP) has similar properties with FBRNDP, thus, making the formulation of MTSP to be adoptable for feeder bus routes. In this study, a bi-level heuristic algorithm is developed to solve this problem by clustering demand nodes around nearest destination and using genetic algorithm (GA) based on fixed start MTSP to optimize the shortest distance the salesmen will have to travel to cover the service area. The algorithm compares well to the results of a case study found in literature and shows a promising way of designing feeder bus routes strictly based on the shortest distance and variation of the number of routes required. The proposed method can be useful in the initial planning of an integrated transit system and it may serve as a seed solution in a multi-objective optimization.