Meilita Tryana Sembiring, Novika Zuya, Muhammad Riezky Anindhitya Laksmana, M. Zaky Hadi
Logistics efficiency is critical to operational success in manufacturing, especially for corrugated carton manufacturers. The challenges of this type of manufacturing include optimizing truck utilization, without which high costs, resource waste, and customer dissatisfaction can occur. Transportation consolidation can reduce trips, increase vehicle capacity, and lower carbon emissions. This study proposes a delivery optimization model using genetic algorithms within the Multi-Objective Evolutionary Algorithm (MOEA) framework. The results show that the model significantly improves fleet utilization from 75% to 100% and reduces delivery delays by adhering to predefined time windows, thereby improving cost efficiency and customer satisfaction. © 2025 by the authors.
Department of Industrial Engineering, Faculty of Engeering, Universitas Sumatera Utara, Medan, 20155, Indonesia; Post Graduate School of Industrial Engineering, Faculty of Engeering, Universitas Sumatera Utara, Medan, 20155, Indonesia; Magister Management, Faculty of Economy and Business, Universitas Prasetiya Mulya, Tangerang, 15399, Indonesia; Department of Industrial Engineering, Faculty of Industrial Technology, Institut Teknologi Sumatera, Lampung Selatan, 35365, Indonesia
Research at a Glance
Register to unlock
Topics & SDG Alignment
Register to unlock
Collaboration
Register to unlock
Author Profile (Selected)
Register to unlock
References Overview
Register to unlock
Journal & Source
Register to unlock
Metadata & Integrity
Register to unlock