A Bi-objective stochastic programming model for the household waste collection and transportation problem: case of the city of Sousse

This paper’s aim is to develop a model for the household waste collection and transportation problem in the city of Sousse, one of the largest cities in Tunisia. Several vehicles with a finite capacity are located at the depot. The vehicles must collect the waste accumulated in all bins. The waste i...

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Vydané v:	Operational research Ročník 21; číslo 3; s. 1613 - 1639
Hlavní autori:	Jammeli, Haifa, Argoubi, Majdi, Masri, Hatem
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2021 Springer Nature B.V
Predmet:	Algorithms Bins Business and Management Cluster analysis Clustering Computational Intelligence Costs Economic impact Environmental impact Finite capacity Garbage collection Goal programming Impact analysis Management Science Normal distribution Operations Research Operations Research/Decision Theory Optimization Original Paper Route selection Stochastic models Stochastic programming Transportation problem Vector quantization Vehicles Vehicle-routing problem and assignment problem Household waste management Multiple objective stochastic programming
ISSN:	1109-2858, 1866-1505
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Popis
Shrnutí:	This paper’s aim is to develop a model for the household waste collection and transportation problem in the city of Sousse, one of the largest cities in Tunisia. Several vehicles with a finite capacity are located at the depot. The vehicles must collect the waste accumulated in all bins. The waste is then delivered to a transfer center, before vehicles return to the depot. The proposed model determines the routes of the vehicles and the number of bins to be assigned to each potential location, while minimizing the collection costs and the environmental impact. The problem can be considered as a bi-objective optimization problem, as cost minimization will be ensured by the optimal assignment of the determined minimum number of bins. We also consider the stochastic aspect of population size, which is supposed to follow a normal distribution. Our model is then a stochastic bi-objective programming model. A solution is obtained with reasonable computational effort using a hierarchical approach consisting of two stages as “cluster-first route-second”. In the first stage, a set of n locations of bins is assigned into k disjoint clusters using the K-means clustering algorithm. In the second stage, a certainty equivalent program to the bi-objective stochastic program is proposed, based on a chance-constrained, recourse and a goal programming approach. The model is tested and implemented using real data from the municipality of Sousse. The study shows that our model leads to lower environmental impact and an almost 38% reduction in the economic costs.
Bibliografia:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ISSN:	1109-2858 1866-1505
DOI:	10.1007/s12351-019-00538-5