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Material Requirements Planning Model Using Multi-Objective Mixed-Integer Linear Programming in a Bicycle Assembly Plant

10.24050/reia.v23i46.1906
Published 2026-09-17
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Abstract

This research presents a material requirements planning (MRP) model using mixed-integer linear programming, with a multi-objective approach, applied to a theoretical bicycle assembly environment. This model is aimed at improving production scheduling in order to ensure demand fulfillment while reducing costs in the production system and maximizing the use of installed capacity. Accordingly, a methodology structured in three phases was adopted. The first consisted of a literature review and formulation of the case study, identifying operational and structural parameters; the second aimed to formulate a compromise-based mixed-integer linear programming model; and, finally, the model was implemented and evaluated in the AMPL IDE environment, using the CPLEX solver. The model proposed in this case study achieved all three key objectives: reducing total costs, minimizing the amount of unmet demand, and maximizing total production over the modeled time horizon (24 weeks). The balanced solution yielded a BALNOR objective value of 0.84; furthermore, 100% demand fulfillment was achieved, with a total production capacity of 4,568 units of finished product. Likewise, total costs were kept at 15,189,080 monetary units. These results validated the model's applicability as an important decision-support tool in this bicycle assembly context. It is concluded that combining MRP with multi-objective optimization techniques greatly improves system performance, enabling more robust, adaptable, and efficient solutions for organizations.

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