A Soft Computing–Based Decision Support Framework Integrating GIS, FAHP, WLC, and TOPSIS for Sustainable Solid Waste Management Planning

The proposed decision framework adopts a deliberately modular structure in which criterion weighting, spatial modelling, and alternative ranking are treated as independent analytical stages, thereby eliminating functional redundancy and reducing computational uncertainty. Uncertainty in expert judgment is addressed solely during the weighting phase through the application of the Fuzzy Analytic Hierarchy Process, ensuring that ambiguity does not propagate into subsequent spatial analyses. Spatial suitability is then modeled using a constrained Weighted Linear Combination approach that produces a continuous surface reflecting ecological and planning limitations. Rather than ranking individual grid cells, final prioritization is conducted at the decision-support level using the Technique for Order Preference by Similarity to Ideal Solution, where candidate locations are assessed as discrete, implementable planning entities. To safeguard the integrity of the results, sensitivity testing is intentionally restricted to the final ranking stage, preventing distortion of the spatial evaluation process. The framework is demonstrated using municipality-scale data, confirming its potential as a transparent, replicable, and technology-oriented decision support approach for solid waste management planning. A case-based implementation using municipal-scale spatial data is included to demonstrate the practical applicability and robustness of the proposed framework.

Decision Support System, Soft Computing, Fuzzy AHP, GIS-Based Analysis, TOPSIS, Weighted Linear Combination, Solid Waste Management, Sensitivity Analysis

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