4.7 Article

Interval-parameter chance-constrained programming model for uncertainty-based decision making in tire retreading industry

Journal

JOURNAL OF CLEANER PRODUCTION
Volume 167, Issue -, Pages 1490-1498

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2016.10.122

Keywords

Used tires; Retreading; Management; Chance-constrained programming; Interval-parameter programming; Uncertainty

Funding

  1. Ministry of Education, Science and Technological Development of the Republic of Serbia [TR 36006]

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Tire retreading is an economically attractive and environmentally beneficial process for extending the lifetime of used tires. It reduces the negative influence of used tires on the environment as well as natural resources exploitation. According to the latest data, 4.7 million units of used truck tires were retreaded in 2014 in Europe. This paper proposes an interval-parameter chance-constrained programming model for uncertainty-based decision making in tire retreading industry. A case study is conducted in order to demonstrate its potentials and applicability. When constraints violation level increases (0.01, 0.05 and 0.10), the system profit obtained in the analyzed nine-year planning horizon correspondingly raises ((sic)[35.08, 82.03] x 10(6), (sic)[38.94, 90.78] x 10(6) and (sic)[40.87, 95.16] x 10(6) respectively). The uncertainty degree of the objective function under three considered system violation levels is around 80%, which demonstrates that used tires retreading management systems are highly uncertain. Profit per tonne of processed used tires is in (sic)[1594.64, 3730.84] interval. The developed model can efficiently handle uncertainties expressed as interval values and probability distributions. It can address multiple interrelationships among numerous components of used tires retreading management systems. The proposed model can examine various admissible risk levels of violating retreading capacities. It can provide a trade-off between economic efficiency of tires retreading management systems and capacity constraints violations. Compared with the conventional chance-constrained programming approach, the formulated model can incorporate much more uncertain information. The presented model can provide valuable support for tire retreading managers in avoiding inferior or simply wrong decisions. In fact, it can help tire retreading managers optimize long-term purchasing, retreading and inventory planning schemes, and allocation patterns of retreaded, reusable and end-of-life tires under multiple uncertainties. The proposed model can be extended to other environmental problems related to part worn or worn-out products. (C) 2016 Elsevier Ltd. All rights reserved.

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