Developing a decision-support Tool for agricultural residue treatment in Hanoi, Vietnam using an integrated Multi-Criteria and life-cycle-oriented approach

Agricultural-residue technology selection requires decision makers to reconcile environmental burdens, financial feasibility, technical practicality, and rural employment under locally incomplete data. This study develops a transparent decision-support framework that links life-cycle thinking with direction-aware min-max normalization, objective Entropy weighting, and TOPSIS to compare five treatment configurations (A0-A4) for rice straw and cattle manure in the former Ba Vi district of Hanoi. The comparison uses annual plant-level environmental, energy, cost, and employment indicators together with project-level net present value and internal rate of return. In the base case, A0 (steam explosion, anaerobic digestion, and combined heat and power) ranks first (Ci = 0.652), narrowly ahead of A3 (digestate pyrolysis and biochar; Ci = 0.650), followed by A4, A1, and A2. Alternative weighting profiles show that A3 becomes first under equal, environmental-priority, and economic-priority weights, whereas A2 becomes first only under a strongly social-priority profile. In a reproducible 10,000-run input stress test using independent +/-10% perturbations and recalculated Entropy weights, A3 ranks first in 68.6% of runs and A0 in 27.8%. The evidence therefore supports A0 as the base-case screening option and A3 as a near-tied strategic alternative, rather than identifying an unconditionally optimal solution. The contribution is a reproducible Hanoi-oriented screening workflow that makes system boundaries, data provenance, trade-offs, and ranking sensitivity explicit; it is not presented as a full ISO-compliant LCA or field-performance validation.