An integrated fuzzy AHP-TOPSIS and NSGA-II approach for EOL recycling strategy

The increasing concern for sustainability and longing for transition into circular economy (CE) has fostered immense interest towards designing an optimal supply chain network with significant sustainability and CE influence. Consequently, this study aims to design a model that can guides the EOL recycling strategy for the end-of-life (EOL) tire to maximise the CE and sustainability outcome. The EOL recycling strategy is a multi-criteria decision-making problem. The fuzzy set theory is employed due to the presence of vagueness and imprecision of information. The novelty of the model rests on its quantification of both the CE and sustainability criteria and on the uses of fuzzy AHP–TOPSIS for modelling the multi-criteria perspectives of the stakeholders. Numerical weights obtained using fuzzy AHP for both CE and sustainability are use as input into fuzzy TOPSIS to rank the alternatives. The outputs are utilised in the modelling of a multi-objective linear programming (MOLP), with the goals of maximising CE and sustainability outcome, subjected to the demands and capacity constraints. Non-sorting genetic algorithm (NSGA-II) is utilised to solve the MOLP and yield properly efficient solutions, providing a trade-off set for conflicting objectives. The significance of the model is demonstrated as a decision support tool for improving the CE and sustainability outcome in an experimental evaluation using numerical example. Practical and theoretical implications are derived from the result analysis, and a generalised model can be effectively adapted by other recyclable EOL products to increase their sustainability and CE outcome.