Universal Journal of Agricultural Research Vol. 14(2), pp. 37 - 47
DOI: 10.13189/ujar.2026.140201
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Optimizing Sustainable Inventory Management in the Animal Feed Industry

Kago Dintwe , Glen Regomoditswe Kube , Lone Seboni ^*
Mechanical Engineering Department, Faculty of Engineering and Technology, University of Botswana, Botswana

ABSTRACT

This research addresses the critical intersection of operational efficiency and environmental sustainability within the agri-manufacturing sector, specifically focusing on the animal feed industry in developing economies. Characterized by high physical perishability of organic raw materials and significant market volatility, the industry necessitates advanced inventory control mechanisms to mitigate financial leakage and environmental degradation. A mixed-methods study involving interviews with stock controllers and operations managers (using purposive sampling), survey questionnaires with 380 customers/farmers (using random sampling), a time study, and a focus group with 10 employees was employed. This study develops a multi-objective optimization framework that integrates non-instantaneous deterioration modelled via a two-parameter Weibull distribution with stock-dependent demand dynamics. Uniquely, the model internalizes carbon emission taxation across ordering, holding, and disposal activities, aligning economic profit with decarbonization goals. A meta-heuristic solution procedure utilizing an elitist Genetic Algorithm is employed to resolve the non-linear, multi-dimensional objective functions. Calibrated with empirical data from a prominent agricultural feed manufacturer, the results reveal that a sustainable lean policy reduces spoilage costs by 45% and carbon footprints by 21%, while simultaneously enhancing total annual profitability by 14.2%. The contribution lies in bridging the implementation gap between operations research and shop-floor reality for SMEs, by incorporating a mathematical framework into a validated Python-based decision-support system. The results also provide significant contributions to literature, practice, and policy, offering a scalable roadmap for SMEs to achieve Industry 5.0 standards while bolstering national food security and ecological resilience.

KEYWORDS
Sustainable Inventory Management, Weibull Deterioration, Carbon Emission Taxation, Genetic Algorithm, Animal Feed Industry, Multi-Objective Optimization

Cite This Paper in IEEE or APA Citation Styles
(a). IEEE Format:
[1] Kago Dintwe , Glen Regomoditswe Kube , Lone Seboni , "Optimizing Sustainable Inventory Management in the Animal Feed Industry," Universal Journal of Agricultural Research, Vol. 14, No. 2, pp. 37 - 47, 2026. DOI: 10.13189/ujar.2026.140201.

(b). APA Format:
Kago Dintwe , Glen Regomoditswe Kube , Lone Seboni (2026). Optimizing Sustainable Inventory Management in the Animal Feed Industry. Universal Journal of Agricultural Research, 14(2), 37 - 47. DOI: 10.13189/ujar.2026.140201.