Execution time as a key parameter in the waste collection problem
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abstract
Proper waste management has been recognized as a
tool for the green transition towards a more sustainable economy.
For instance, most studies dealing with municipal solid wastes in
the literature focus on environmental aspects, proposing new
routes for recycling, composting and landfilling. However, there
are other aspects to be improved in the systems that deal with
municipal solid waste, especially in the transportation sector.
Scholars have been exploring alternatives to improve the
performance in waste collection tasks since the late 50s, for
example, considering the waste collection problem as static. The
transition from a static approach to a dynamic is necessary to
increase the feasibility of the solution, requiring faster algorithms.
Here we explore the improvement in the performance of the
guided local search metaheuristic available in OR-Tools upon
different execution times lower than 10 seconds to solve the
capacitated waste collection problem. We show that increasing the
execution time from 1 to 10 seconds can overcome savings of up to
1.5 km in the proposed system. Considering application in
dynamic scenarios, the 9 s increase in execution time (from 1 to 10
s) would not hinder the algorithm’s feasibility. Additionally, the
assessment of the relation between performance in different
execution times with the dataset’s tightness revealed a correlation
to be explored in more detail in future studies. The work done here
is the first step towards a shift of paradigm from static scenarios
in waste collection to dynamic route planning, with the execution
time established according to the conclusions achieved in this
study.
This work has been supported by FCT—Fundação para a
Ciência e a Tecnologia within the R&D Units Project Scope:
UIDB/05757/2020, UIDP/05757/2020, UIDB/00690/2020,
UIDB/50020/2020, and LA/P/0007/2021. Adriano Silva was
supported by FCT-MIT Portugal Ph.D. grant
SFRH/BD/151346/2021.
