Optimizing Agro-Infrastructural Security and Disaster Readiness: A Constrained Fuzzy Multi-Objective Goal Programming Approach to Workforce Performance Planning in the Nigerian Security and Civil Defence Corps

Nigeria’s agricultural sector and associated critical infrastructure face overlapping threats from vandalism, climate-induced disasters, and terrorism. Although the Nigerian Security and Civil Defence Corps (NSCDC) is mandated to protect these assets, its workforce performance planning remains largely heuristic. This study develops a constrained fuzzy multi-objective goal programming (CFMOGP) model to optimize workforce resource allocation in the NSCDC South-West zone. Summary statistics from 60 Likert-scale items administered to 191 respondents were transformed into fuzzy membership scores. The model integrates three competing objectives: operational and anti-vandalism efficiency, disaster and terrorism response readiness, and workforce motivation. Analytical proofs establish the existence of a Pareto-optimal fuzzy solution and its Lipschitz continuity under fiscal perturbations. The Analytic Hierarchy Process (AHP) was used to inform baseline, specialized, and balanced policy scenarios, followed by sensitivity analysis involving a 10% fiscal shock. Under the modeled conditions, the results identify a hybrid policy combining a 26% minimum welfare allocation with a 45% protected allocation for information and communication technology and disaster training as the optimal strategy for securing agricultural infrastructure while maintaining institutional viability. These findings support coordinated investment in workforce welfare, technological capacity, and emergency preparedness within constrained budgets. The study provides a mathematically tractable framework for balancing competing workforce priorities and informing resource allocation for paramilitary security and disaster readiness.

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Publication Details

Journal
Mikailalsys Journal of Mathematics and Statistics
Published
2026-10-31
DOI
https://doi.org/10.58578/mjms.v4i3.11848
Primary Topic
Optimization and Mathematical Programming
Type
article
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article

Optimizing Agro-Infrastructural Security and Disaster Readiness: A Constrained Fuzzy Multi-Objective Goal Programming Approach to Workforce Performance Planning in the Nigerian Security and Civil Defence Corps

Obia Gopeh Inyang, Abam Ayeni Omini, Blessing George Abam, Christopher Eraye Michael et al.
Mikailalsys Journal of Mathematics and Statistics
Optimization and Mathematical Programming
article

Optimizing Agro-Infrastructural Security and Disaster Readiness: A Constrained Fuzzy Multi-Objective Goal Programming Approach to Workforce Performance Planning in the Nigerian Security and Civil Defence Corps

Obia Gopeh Inyang, Abam Ayeni Omini, Blessing George Abam, Christopher Eraye Michael, Uchenwa Linus Okafor, Udoh Israel Jacob
article en

Abstract

Nigeria’s agricultural sector and associated critical infrastructure face overlapping threats from vandalism, climate-induced disasters, and terrorism. Although the Nigerian Security and Civil Defence Corps (NSCDC) is mandated to protect these assets, its workforce performance planning remains largely heuristic. This study develops a constrained fuzzy multi-objective goal programming (CFMOGP) model to optimize workforce resource allocation in the NSCDC South-West zone. Summary statistics from 60 Likert-scale items administered to 191 respondents were transformed into fuzzy membership scores. The model integrates three competing objectives: operational and anti-vandalism efficiency, disaster and terrorism response readiness, and workforce motivation. Analytical proofs establish the existence of a Pareto-optimal fuzzy solution and its Lipschitz continuity under fiscal perturbations. The Analytic Hierarchy Process (AHP) was used to inform baseline, specialized, and balanced policy scenarios, followed by sensitivity analysis involving a 10% fiscal shock. Under the modeled conditions, the results identify a hybrid policy combining a 26% minimum welfare allocation with a 45% protected allocation for information and communication technology and disaster training as the optimal strategy for securing agricultural infrastructure while maintaining institutional viability. These findings support coordinated investment in workforce welfare, technological capacity, and emergency preparedness within constrained budgets. The study provides a mathematically tractable framework for balancing competing workforce priorities and informing resource allocation for paramilitary security and disaster readiness.

Mikailalsys Journal of Mathematics and StatisticsVol. 4(3)
Openalex Percentile: Top 17%
Optimization and Mathematical Programming
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