Abstract

The Brazilian Institute of Geography and Statistics (IBGE) periodically conducts the Census of Agriculture (CA), which investigates information on agricultural establishments nationwide. The latest CA editions were characterized by technological innovation. In the 2006 CA, paper questionnaires were replaced with electronic ones embedded in mobile devices, which also enabled the collection of geographic coordinates of every establishment. The subsequent CA (2017) introduced new mechanisms: an a priori establishment list (fed with previous CA data), satellite images in the mobile devices to help enumerators locate themselves in the field, and the recording of geographic coordinates of the enumerators' trajectories. For the forthcoming CA editions, IBGE is developing more advanced analytics solutions, using optimization techniques to enhance field operations performance and provide managers with valuable information to improve decision-making, operations monitoring, and assessment. A fundamental proposal in this context is systematically adopting a hierarchical structure for organizing data collection units. Past CA editions had a two-level organization: the data collection units (every agricultural establishment) and enumeration areas (territorial units for data collection). The fieldwork of an enumerator during the CA involves traversing every pathway within an enumeration area. Accordingly, an intermediate level shall be introduced in that hierarchical organization: pathway sections. The idea is to map every trafficable pathway (road, footpath, waterway, etc.) within each enumeration area and subdivide them into sections. A pathway section can be defined as each segment of a pathway delimited by that pathway endpoints or points of intersection with other pathways or with the border of the enumeration area that contains it. This new hierarchical organization allows the application of more precise metrics to measure data collection progress and coverage based on the proportion of completed pathway sections. Enhancing precision in operations monitoring also allows faster detection of productivity issues, enabling managers to respond timely. Another proposal, which builds upon the pathway sections network, is replacing the manual route planning process applied in past CA editions with an automated process based on optimization techniques. The literature shows that moving from a manual routing process to an optimization-driven automated routing process can reduce transportation costs by 10% to 30%, besides significantly increasing productivity. Specifically, the idea is to model the CA data collection scenario as an Arc Routing Problem, where the goal is to find optimized routes for traversing every pathway section with potential agricultural establishments within each enumeration sector. Multiple objectives are considered in this optimization problem. The primary objective is to minimize operational costs, including travel distances, overnight stays, field operations duration, etc. A second one is to minimize regional consistency, i.e., varying enumerators assigned routes in each region. The latter aims to bring uniformity to data collection by dispersing the effects of individual enumerators' behavior across different areas. A third objective is to maximize workload equity by varying the characteristics (density, trafficability, etc.) of routes assigned to each enumerator. Despite the challenges posed by implementing these proposals, their potential benefits outweigh the required efforts, and we expect to observe and report concrete results soon.