Authors :
Chikezie Bethel Uchechukwu; Ogbonnia Kingsley Chibuzo
Volume/Issue :
Volume 11 - 2026, Issue 7 - July
Google Scholar :
https://tinyurl.com/ycy3a8zs
Scribd :
https://tinyurl.com/msy5tewh
DOI :
https://doi.org/10.38124/ijisrt/26jul1523
Note : A published paper may take 4-5
working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and
ResearchGate.
Abstract :
The Sustainable Development Goals (SDGs) form an indivisible agenda, yet policy design and implementation
remain dominated by sector-specific programmes that can generate unrecognized spillovers, delayed effects and burden
shifting. This study develops a dynamic systems-of-systems (SoS) decision-support framework that represents all 17 SDGs
as operationally distinct but interdependent constituent systems. The framework integrates a signed and directed interaction
matrix, causal-loop analysis, stock-flow system dynamics, seven cross-sector policy levers, constrained multi-objective
optimization and Monte Carlo uncertainty analysis. A transparent proof-of-concept application uses normalized goal-level
states and literature-informed interaction directions to compare business-as-usual, siloed growth, green-transition, humandevelopment and optimized SoS portfolios over 2025-2035. The optimized portfolio increases the mean normalized SDG
score from 0.601 under business-as-usual to 0.710 by 2030 and from 0.693 to 0.835 by 2035. It also raises the weakest-goal
score from 0.452 to 0.631 by 2030 and from 0.512 to 0.753 by 2035. In contrast, the siloed-growth scenario improves the
aggregate score but depresses the weakest-goal and environmental outcomes, demonstrating that aggregate progress can
conceal systemic deterioration. Network out-strength identifies SDGs 16, 4, 17, 13 and 5 as high-leverage goals. Across 1,000
uncertain parameter realizations, the optimized portfolio retains a narrow 2035 mean-score interval of 0.829-0.840. The
numerical results are illustrative rather than forecasts, but they demonstrate how systems engineering can convert
qualitative SDG interlinkage knowledge into an auditable, adaptive and optimization-ready policy architecture.
Keywords :
Sustainable Development Goals; Systems-of-Systems; Systems Engineering; System Dynamics; Causal-Loop Diagram; Policy Coherence; Multi-Objective Optimization; Uncertainty Analysis; Leverage Points.
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The Sustainable Development Goals (SDGs) form an indivisible agenda, yet policy design and implementation
remain dominated by sector-specific programmes that can generate unrecognized spillovers, delayed effects and burden
shifting. This study develops a dynamic systems-of-systems (SoS) decision-support framework that represents all 17 SDGs
as operationally distinct but interdependent constituent systems. The framework integrates a signed and directed interaction
matrix, causal-loop analysis, stock-flow system dynamics, seven cross-sector policy levers, constrained multi-objective
optimization and Monte Carlo uncertainty analysis. A transparent proof-of-concept application uses normalized goal-level
states and literature-informed interaction directions to compare business-as-usual, siloed growth, green-transition, humandevelopment and optimized SoS portfolios over 2025-2035. The optimized portfolio increases the mean normalized SDG
score from 0.601 under business-as-usual to 0.710 by 2030 and from 0.693 to 0.835 by 2035. It also raises the weakest-goal
score from 0.452 to 0.631 by 2030 and from 0.512 to 0.753 by 2035. In contrast, the siloed-growth scenario improves the
aggregate score but depresses the weakest-goal and environmental outcomes, demonstrating that aggregate progress can
conceal systemic deterioration. Network out-strength identifies SDGs 16, 4, 17, 13 and 5 as high-leverage goals. Across 1,000
uncertain parameter realizations, the optimized portfolio retains a narrow 2035 mean-score interval of 0.829-0.840. The
numerical results are illustrative rather than forecasts, but they demonstrate how systems engineering can convert
qualitative SDG interlinkage knowledge into an auditable, adaptive and optimization-ready policy architecture.
Keywords :
Sustainable Development Goals; Systems-of-Systems; Systems Engineering; System Dynamics; Causal-Loop Diagram; Policy Coherence; Multi-Objective Optimization; Uncertainty Analysis; Leverage Points.