Research pick: Green shoots point to improving urban waste management - "Adaptation of plant propagation algorithm for waste collection vehicle routing problem"

Operational efficiency often leads to environmental compromise in solid waste management. An approach discussed in the International Journal of Applied Decision Sciences proposes an innovative approach that could improve the collection and transportation of municipal waste. The researchers have turned to the Plant Propagation Algorithm (PPA), a nature-inspired computational method, for a different perspective on routing waste collection vehicles.

Urban sanitation services need vehicles to traverse the city as efficiently as possible. But, working out the schedules and routes many vehicles need to take is no simple planning matter. Vehicles obviously have limited waste capacity, traffic conditions vary, and there are collection time windows with which to contend in terms of access. Moreover, all vehicles need to offload their waste several times on a single shift.

As urban populations grow and waste volumes rise, solving this logistical puzzle becomes increasingly difficult, especially using conventional logistics-planning methods. Many of these traditional approaches are heuristic in nature, which means they are essentially rule-of-thumb. Metaheuristics on the other hand used advanced algorithms based on biological or physical processes. These can efficiently search large sets of possible solutions to find the most viable ones.

The Plant Propagation Algorithm stands out among these tools. It draws its logic from the way strawberry plants reproduce: by sending out runners, some explore nearby soil, others venture further afield, to find ideal growing locations for new plants to grow. This metaphor is converted into a computational search strategy that can balance local and global exploration in the space of potential vehicle routes.

The team created benchmark scenarios using the algorithm and determined performance against criteria such as total distance travelled, fuel usage, the number of vehicles required, and driver working hours. The algorithm was able to generate feasible solutions despite the complexities of urban waste systems anc could handle variable service schedules, diverse waste types, and geographically irregular service zones.

Mat, N.A., Benjamin, A.M., Abdul-Rahman, S., Ku-Mahamud, K.R. and Ramli, M.F. (2025) ‘Adaptation of plant propagation algorithm for waste collection vehicle routing problem’, Int. J. Applied Decision Sciences, Vol. 18, No. 4, pp.383–407.