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All Journal Journal of Engineering and Management in Industrial System
Salsabila, Dhia Naqqiya
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Industrial & Manufacturing Engineering

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OPTIMIZATION OF FLEET UTILIZATION AND WAITING TIME IN SUPPLY CHAIN AGENT-BASED SIMULATION USING REINFORCEMENT LEARNING Tama, Ishardita Pambudi; Sujarwo, Sujarwo; Hardiningtyas, Dewi; Nugroho, Willy Satrio; Salsabila, Dhia Naqqiya
JEMIS (Journal of Engineering & Management in Industrial System) Vol. 12 No. 1 (2024)
Publisher : Industrial Engineering Department, Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/

Abstract

Inventory to transport transition was a critical operation that requires high efficiency in manufacturing. This study models the inventory transition of manufacturing plants in a supply chain network. The objective was to configure the minimum fleet utilization with fastest waiting time.  The configuration was performed using reinforcement learning assisted agent-based model (ABM) simulation. The ABM with fleet speed control have the best performance with average waiting time of 5.84 hours with lowest fleet utilization which surpasses other models. Lower fleet and waiting time provide rest periods for the driver. Therefore, performing speed control during transport improves human factor of the supply chain operation.
OPTIMIZING SUPPLY CHAIN STRATEGIES THROUGH COMPETITION BETWEEN LOCAL AND EXTERNAL SUPPLIERS salsabila, Dhia Naqqiya; Debrina Puspita Andriani; Rakhmat Himawan
JEMIS (Journal of Engineering & Management in Industrial System) Vol. 13 No. 2 (2025): In Process
Publisher : Industrial Engineering Department, Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/

Abstract

This study analyzes the optimization of supply chain strategies in the context of competitive interactions between local and external suppliers within the souvenir food retail industry in Indonesia. Motivated by increasing demand due to tourism growth and supply uncertainties in traditional sourcing, this research develops a two-echelon game-theoretic supply chain model involving one manufacturer and two suppliers. The study incorporates three competition scenarios: a Stackelberg game with the local supplier as leader, a Stackelberg game with the external supplier as leader, and a Nash game where both suppliers act simultaneously. The model considers yield uncertainty in production and consumer preference for product quality, which affects demand and pricing decisions. The manufacturer’s learning cost from using unfamiliar external materials is also modeled. Analytical solutions are derived using backward induction and equilibrium analysis, and numerical simulations are conducted based on real data from coconut sourcing in West Java. The results show that supplier leadership significantly affects wholesale pricing and procurement decisions. Moreover, increasing consumer preference for quality enhances the competitiveness of external suppliers but raises procurement and learning costs. The Nash scenario provides a balanced outcome, while Stackelberg scenarios yield more favorable results depending on the dominant supplier. This research contributes to supply chain theory by incorporating consumer preference, learning cost, and yield uncertainty in a game-theoretic framework. Practically, it offers strategic recommendations for manufacturers to diversify supply and improve resilience in response to demand volatility and market competition.
Co-Authors Debrina Puspita Andriani Dewi Hardiningtyas Ishardita Pambudi Tama Rakhmat Himawan Sujarwo Sujarwo Willy Satrio Nugroho