A SIMPLIFIED ONLINE SOLUTION FOR SIMULATION-BASED OPTIMIZATION OF EARTHMOVING OPERATIONS
Daily field management of earthmoving operations requires quick and regular decisions for allocating available equipment to different jobs on a project. A general foreman’s day starts with matching several activities with a suitable set of available equipment to achieve the highest productivity and lowest unit cost. Usually, this decision-making process needs to be quick, and depends to a great extent on the foreman’s experience, which varies from one individual to another. Many analytical solutions with various degrees of sophistication and optimization exist to address such decisions. However, adopting any of these solutions is contingent on how accessible and easy-to-use the solution is. This paper discusses the development process of a webaccessible solution for evaluating earthmoving fleet composition and allocation scenarios. The solution relies on discrete event simulation and an optimization backend engine, but introduces the user with a simplified and easy-to-use interface that is accessible from any mobile device, and is customized to specific user’s needs. The developed system gathers most equipment and site-related input data from a company’s information systems to minimize user input. The user mainly needs to formulate equipment and job combinations and allocation scenarios (e.g. soil type, quantity, and hauling distance), according to equipment availability each day. Then the system will evaluate the productivity and unit cost estimates for each scenario, allowing the user to choose the most suitable one. It may also be used to automatically recommend the optimum solution given an available list of equipment. The paper presents the process followed in prototyping the proposed system in collaboration with a major Canadian earthmoving contractor, and customizing it to the user needs within the company. It also describes the overall structure of the developed system and its core simulation model.
Simulation; Simulations; Simulation; Operation; Trucks; Truck; Productivity; Costs; Cost; optimization;