Interval-parameter semi-infinite programming model for used tire management and planning under uncertainty

In the European Union, approximately 3.6 million tonnes of used tires are generated annually. Because used tires are not biodegradable, there is strong motivation to successfully manage this fast-growing waste flow. One of the most popular approaches for sustainable environmental stewardship of used tires is retreading. The problem investigated in this paper is to identify optimized purchasing, retreading, and inventory planning schemes of used tires in multiple tire retreading plants as well as allocation patterns of retreaded, reusable, and end-of-life tires that secure maximized profit within a multi-period planning horizon and under multiple uncertainties. This paper proposes an interval-parameter semi-infinite programming model for used tire management and planning. The underlying difference between this model and those developed in previous research is its ability to consider the effects of external impact factors related to complicated economic, environmental, and social activities on used tire management systems. Moreover, it can successfully handle real-life uncertainties of the used tire management systems expressed as functional and crisp intervals. A numerical example is provided to demonstrate the usefulness of the developed model. Flexible long-term purchasing, retreading, inventory, and allocation plans, which are adjustable with variations of external impact factors, are obtained. The presented model has advantages in addressing the dynamic complexity of used tire management systems by introducing the functional interval parameters associated with the price of a new tire as well as electricity and gas prices and labor costs in waste management and transportation sectors. Compared with the available models, the resulting solutions are far more robust because they are able to satisfy all possible levels of external impact factors. The presented model is beneficial for the tire retreading industry, which processes millions of used tires annually. (C) 2017 Elsevier Ltd. All rights reserved.