An Integrated Multi-Criteria Decision-Making Framework for Supervisory Control System Design in Smart Municipal Solid Waste Management

Résumé fourni par la source

The transition of municipal solid waste (MSW) management from periodic, manually scheduled operations to continuously monitored, data-driven systems require a decision layer capable of converting heterogeneous sensor and operational data into reliable control actions. This study proposes and computationally validates an integrated multi-criteria decision-making (MCDM) framework as the cognitive decision layer of a four-layer supervisory control architecture comprising sensing, edge/communication, cognitive decision, and actuation layers. Eight criteria covering economic, environmental, technical, social, and control dimensions, including control-loop responsiveness and data-integration scalability, are used to evaluate five representative MSW management alternatives: sanitary landfilling, waste-to-energy incineration, material recovery facilities, composting/anaerobic digestion, and an Internet of Things (IoT)-enabled smart integrated recovery system. Criterion weights are determined using a hybrid approach combining the subjective Analytic Hierarchy Process (AHP) and objective Shannon entropy method, achieving a strong AHP consistency ratio (CR = 0.0047). The resulting weights are applied to three independent ranking methods: TOPSIS, VIKOR, and PROMETHEE II. Their results are consolidated using Borda rank aggregation and evaluated through Spearman rank-correlation analysis. All three methods consistently identify the IoT-enabled smart integrated recovery system as the best alternative, with TOPSIS, VIKOR, and PROMETHEE II values of CC = 0.7045, Q = 0.000, and net flow = 0.3665, respectively. A one-at-a-time sensitivity analysis with ±30% weight perturbations confirms the stability of the top-ranked alternative. The complete computational pipeline is implemented in open, reproducible Python code. The proposed framework provides control and environmental engineers with a transparent and auditable approach for integrating multi-criteria reasoning into real-time MSW management and identifying criteria requiring careful practical assessment.

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