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

Author

Listed:
  • Haifa Jammeli

    (Institute of Higher Studies Tunis)

  • Majdi Argoubi

    (University of Sousse)

  • Hatem Masri

    (University of Bahrain)

Abstract

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.

Suggested Citation

  • Haifa Jammeli & Majdi Argoubi & Hatem Masri, 2021. "A Bi-objective stochastic programming model for the household waste collection and transportation problem: case of the city of Sousse," Operational Research, Springer, vol. 21(3), pages 1613-1639, September.
    • Handle: RePEc:spr:operea:v:21:y:2021:i:3:d:10.1007_s12351-019-00538-5
    DOI: 10.1007/s12351-019-00538-5
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    References listed on IDEAS

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    1. Toso, Eli Angela V. & Alem, Douglas, 2014. "Effective location models for sorting recyclables in public management," European Journal of Operational Research, Elsevier, vol. 234(3), pages 839-860.
    2. Listes, Ovidiu & Dekker, Rommert, 2005. "A stochastic approach to a case study for product recovery network design," European Journal of Operational Research, Elsevier, vol. 160(1), pages 268-287, January.
    3. K. Ganesh & T.T. Narendran, 2007. "CLASH: a heuristic to solve vehicle routing problems with delivery, pick-up and time windows," International Journal of Services and Operations Management, Inderscience Enterprises Ltd, vol. 3(4), pages 460-477.
    4. Surya Sahoo & Seongbae Kim & Byung-In Kim & Bob Kraas & Alexander Popov, 2005. "Routing Optimization for Waste Management," Interfaces, INFORMS, vol. 35(1), pages 24-36, February.
    5. Richard Bellman, 1954. "On some applications of the theory of dynamic programming to logistics," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 1(2), pages 141-153, June.
    6. Ganesh, K. & Narendran, T.T., 2007. "CLOVES: A cluster-and-search heuristic to solve the vehicle routing problem with delivery and pick-up," European Journal of Operational Research, Elsevier, vol. 178(3), pages 699-717, May.
    7. Yunna Wu & Meng Yang & Haobo Zhang & Kaifeng Chen & Yang Wang, 2016. "Optimal Site Selection of Electric Vehicle Charging Stations Based on a Cloud Model and the PROMETHEE Method," Energies, MDPI, vol. 9(3), pages 1-20, March.
    8. De Meyer, Annelies & Cattrysse, Dirk & Van Orshoven, Jos, 2015. "A generic mathematical model to optimise strategic and tactical decisions in biomass-based supply chains (OPTIMASS)," European Journal of Operational Research, Elsevier, vol. 245(1), pages 247-264.
    9. A. Charnes & W. W. Cooper, 1959. "Chance-Constrained Programming," Management Science, INFORMS, vol. 6(1), pages 73-79, October.
    10. Richard Bellman, 1954. "Some Applications of the Theory of Dynamic Programming---A Review," Operations Research, INFORMS, vol. 2(3), pages 275-288, August.
    11. Robert M. Clark & James I. Gillean, 1975. "Analysis of Solid Waste Management Operations in Cleveland, Ohio: A Case Study," Interfaces, INFORMS, vol. 6(1-part-2), pages 32-42, November.
    12. Abdelaziz, Fouad Ben & Aouni, Belaid & Fayedh, Rimeh El, 2007. "Multi-objective stochastic programming for portfolio selection," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1811-1823, March.
    13. Alçada-Almeida, Luís & Coutinho-Rodrigues, João & Current, John, 2009. "A multiobjective modeling approach to locating incinerators," Socio-Economic Planning Sciences, Elsevier, vol. 43(2), pages 111-120, June.
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