Optimum multipusher-scraper fleets for earthmoving

A probabilistic model is proposed for selecting optimal multipusher-scraper fleets, replacing charts with mathematical equations. As a result, this approach needs fewer machine data and is more efficient in selecting optimal earthmoving fleets. The model optimizes the total project cost instead of unit production cost. Existing simulation programs are used to verify the analytical model developed. Actual field observations are used to develop empirical models of load-growth curves. Scrapers' travel time is analytically estimated. The fleet production is predicted using queuing theory. Manufacturers' cost data are used to develop relationships between project costs and production rates and the independent variables. Sensitivity analysis is performed to analyze impacts of the main variables on the fleet performance.<>