Selection of recycling centre locations by using the interval type-2 fuzzy sets and two-objective genetic algorithm.

Area of Science:

• Operations Research
• Environmental Engineering
• Industrial Engineering

Background:

• Contemporary industrial challenges necessitate efficient recycling solutions.
• Selecting optimal locations for recycling centers is crucial for effective waste management.
• Existing methods may not adequately address the uncertainty inherent in evaluating location attributes.

Purpose of the Study:

• To propose a novel model for selecting locations for new technology-equipped recycling centers.
• To address the multi-objective nature of site selection, considering both distance and suitability.
• To incorporate uncertainty in attribute evaluation using advanced fuzzy set theory.

Main Methods:

• Formulated the location selection as a two-objective optimization problem.
• Utilized interval triangular type-2 fuzzy numbers to model linguistic expressions and uncertainty.
• Developed a procedure for determining an overall suitability index.
• Employed a two-objective genetic algorithm for selecting the most appropriate locations.

Main Results:

• A robust model for recycling center location selection was developed.
• The model effectively integrates fuzzy logic to manage attribute uncertainty.
• A two-objective genetic algorithm proved suitable for optimizing location choices.
• The model's applicability was demonstrated using real-world data from Serbia.

Conclusions:

• The proposed model offers an effective approach to optimizing recycling center site selection.
• The integration of type-2 fuzzy numbers enhances the handling of real-world uncertainties in decision-making.
• The genetic algorithm approach provides an efficient solution for complex routing and location problems in recycling infrastructure planning.