One crucial activity for a company’s long-term sustainability is establishing an effective production planning policy. Currently, CV Lembah Melintang relies on consumer demand to determine its production process, which often leads to suboptimal resource utilization. This research aims to develop an optimal production plan using a Multi-Goal Programming (MGP) model to maximize resource use and increase company income.
The MGP model, an extension of the goal programming method, allows for multiple objectives by incorporating deviation variables to handle conflicts between goals. In this study, the objectives are: maximizing total production, minimizing production costs, and maximizing profit, subject to relevant resource constraints. Data analysis and computation were carried out using POM-QM v5 software.
The results indicate that the production plan successfully met the company’s targets: sales volume was achieved, production costs remained below the target limit of IDR 922,105,662.4, and profit reached the target of IDR 564,080,764 for the 2023 period. The study concludes that the MGP model is an effective decision-support tool for improving production planning policies and aligning multiple strategic goals in manufacturing environments.
H. Cipta, Rina Widyasari· Jurnal Matematika UNAND· 0 citations
Urban waste transportation systems often experience inefficiencies due to uncertainty in daily waste generation, leading to vehicle overloads, increased operational costs, and environmental impacts. This study proposes a robust optimization model for the capacitated vehicle routing problem (RO-CVRP) to explicitly address demand uncertainty in municipal waste collection. A budgeted uncertainty parameter gamma is incorporated to control the level of protection against worst-case deviations. Initial routes are generated using the Clarke-Wright savings (CWS) algorithm and subsequently evaluated within a robust optimization framework. Computational experiments are conducted using real data from temporary disposal sites (TPS) in Tanah Enam Ratus Subdistrict Medan City, with a vehicle capacity of 10 m³. The results show that higher gamma values produce more conservative routing solutions, increasing the number of vehicles while reducing the risk of capacity violations. Price of robustness (PoR) analysis highlights the trade-off between transportation cost and reliability, confirming the model’s effectiveness for resilient waste logistics planning.
