ESSEC METALAB

RESEARCH

OPTIMIZING LEAF SWEEPING AND COLLECTION IN THE ARGENTINE CITY OF TRENQUE LAUQUEN

[ARTICLE] An integer linear programming-based solution strategy has been developed for leaf sweeping operations in Trenque Lauquen, Argentina, optimizing sweeper assignments, leaf bag deposit points, and collection truck routes.

by Diego Delle Donne (ESSEC Business School), Valeria Di Tomaso, Guillermo Duran

A solution strategy based on integer linear programming models has been developed for leaf sweeping operations in the Argentine city of Trenque Lauquen. The aim is to achieve efficiency in the assignment of sweepers to city blocks, the identification of leaf bag deposit points and the routes to be followed by collection trucks for leaf bag pickup. Previous to this strategy, sweeper assignments were improvised and inefficient, with blocks often left unswept. Furthermore, no method was available for accurately determining the number of sweepers needed to ensure either full coverage of all city zones within the working day or a balanced work load distribution across all sweepers. Application of the solution strategy by the city has resulted in efficient definitions of sweeper requirements while optimizing sweeper assignments such that all blocks are covered. Once the strategy is fully implemented, the number of bag deposit points under the manual definitions should be reduced by roughly one-half and the total travel distance of the truck routes, modelled as an asymmetric travelling salesman problem, should be cut by 10–15% with the consequent savings in time, vehicle use and fuel consumption.

[Please read the research paper here]

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