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All Journal International Journal of Electrical and Computer Engineering Journal of the Indonesian Mathematical Society Sinkron : Jurnal dan Penelitian Teknik Informatika Building of Informatics, Technology and Science MES: Journal of Mathematics Education and Science Journal of Research in Mathematics Trends and Technology Journal of Applied Data Sciences
Saib Suwilo
Department of Mathematics, University of Sumatera Utara
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Mathematics

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Journal : Journal of Applied Data Sciences

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A Data-Driven Mixed Integer Nonlinear Programming Model for Cost-Optimal Scheduling of Perishable Production and Workforce Putri, Mimmy Sari Syah; Mawengkang, Herman; Suwilo, Saib; Tulus, Tulus
Journal of Applied Data Sciences Vol 6, No 4: December 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i4.1019

Abstract

This study presents a data-driven, Mixed Integer Nonlinear Programming (MINLP) framework for optimizing the multi-period production scheduling of perishable products with integrated workforce planning. Its primary novelty is the holistic integration of a continuous exponential decay function for product deterioration with dynamic workforce planning, creating a unified model that optimizes production, inventory, and labor simultaneously. This approach addresses key challenges in perishable inventory systems by treating labor as a controllable resource rather than a fixed constraint. Mathematically, the model includes nonlinear inventory balance equations with decay terms and resource-dependent capacity constraints. The objective is to minimize total operational cost, comprising production, holding, and spoilage costs. Computational experiments, based on a realistic case study, demonstrate that the proposed model reduces total system cost by 6.2% and spoilage costs by 43.2% compared to a standard heuristic benchmark. The resulting production and labor schedules align closely with demand fluctuations, supporting both economic and operational efficiency. This unified framework advances the mathematical modeling of sustainable production planning and offers a practical tool for real-world industries such as food processing and pharmaceuticals.
Co-Authors Aghni Syahmarani Aghni Syahmarani Ahmad Zaki Mubarak, Ahmad Zaki Christy, Claudia Efendi, Syahril Elly Rosmaini Erna Budhiarti Nababan Feren, Feren Gayus Simarmata, Gayus Harahap, Desti Alannora Hasibuan, Shubuhan Syukri Herman Mawengkang Mardiansyah, Heru Mardiningsih Mardiningsih , Mardiningsih Mardiningsih Mardiningsih Muhammad Zarlis, Muhammad Nasution, Putri Khairiah Opim Salim Sitompul Pasaribu, Suhendri Prandana, Randy Pujiana, Perli Pulungan, Annisa Fadhillah Putri, Mimmy Sari Syah Rezeki, Ema Sri Riansyah, Muhammad Rizka Fitria, Rizka Rumahorbo, Yuli Sukiman, T. Sukma Achriadi Sutarman Sutarman Tarigan, Aam Jon Mintase Tarigan, Ruffiana Tulus Tulus Yanti, Maulida