The Two-Echelon Vehicle Routing Problem with Drones (2E VRP-D) model can initiate flights from the truck, complete several deliveries to different customer locations, and then rendezvous with the truck again. In addition to economic benefits, logistics providers must consider the environmental impacts of the order-fulfillment process. A novel multi-objective optimization framework is established in this study to simultaneously minimize the total time required for truck travel while also reducing total carbon emissions. Due to restrictions in payload capacity and battery energy limits, drones need to work alongside trucks to deliver services effectively. A dynamic energy consumption model is applied for the drone, where energy use changes based on the loading rate, enabling a more realistic representation of actual operations. This complex problem is addressed using the Non-Dominated Sorting Genetic Algorithm (NSGA-II) with two approaches: the Giant Chromosome (GC) and K-means methods. Routing plans for both trucks and drones are then constructed using a novel heuristic algorithm. Overall, the K-means method delivers better average objective values, reflecting enhanced exploitation performance. Conversely, the GC method produces a higher Hypervolume (HV), indicating superior convergence and coverage of the Pareto front, supported by a lower spacing value, while K-means achieves a slightly better spread. These outcomes contribute to improving logistics operations and informing government policy decisions.
Santoso Santoso, Nurhadi Siswanto, B. Santosa et al.· Engineering, Technology &...· 0 citations
The Gresik Gas Distribution Station (GDS) is a critical natural gas facility operating under high-pressure conditions, where process failures may lead to Major Accident Hazards (MAHs). Therefore, systematic hazard identification is essential to ensure process safety and operational reliability. This study aims to identify potential MAHs and determine the Safety Critical Elements (SCEs) required to prevent and manage these hazards. The study employed the Hazard and Operability Study (HAZOP) method to evaluate three key process nodes: the metering and regulating system, odorant injection system, and instrument air system. Process deviations were analyzed using guide words, followed by risk assessment to identify MAHs. Safety Critical Elements were subsequently identified based on their safety functions, including the prevention, detection, control, mitigation, and recovery of MAH events. The analysis identified 17 potential causes classified as Major Accident Hazards and 76 Safety Critical Elements, grouped into 26 SCE types. Based on the criticality assessment, 4 SCEs were classified as high criticality, 9 as medium criticality, and 13 as low criticality. The most critical SCEs were HC Pipework, Level Indicator, Fixed Point Flammable Gas Detectors, and Flame Detectors. These findings demonstrate that the HAZOP-based approach effectively identifies Major Accident Hazards and establishes priorities for Safety Critical Element management, providing a practical basis for improving process safety and operational reliability in natural gas distribution facilities.
Jasillatul Hikmiyah, D. Dewi, Nurhadi Siswanto· Energy· 0 citations