A Hybrid Optimization Algorithm for Solving of the Unit Commitment Problem Considering Uncertainty of the Load Demand

Unit commitment problem (UCP) is classified as a mixed-integer, large combinatorial, high-dimensional and nonlinear optimization problem. This paper suggests solving the UCP under deterministic and stochastic load demand using a hybrid technique that includes the modified particle swarm optimization (MPSO) along with equilibrium optimizer (EO), termed as MPSO-EO. The proposed approach is tested firstly on 15 benchmark test functions, and then it is implemented to solve the UCP under two test systems. The results are basically compared to that of standard EO and previously applied optimization techniques in solving the UCP. In test system 1, the load demand is deterministic. The proposed technique is in the best three solutions for the 10-unit system with cost savings of 309.95 USD over standard EO and for the 20-unit system it shows the best results over all algorithms in comparison with cost savings of 1951.5 USD over standard EO. In test system 2, the load demand is considered stochastic, and only the 10-unit system is studied. The proposed technique outperforms the standard EO with cost savings of 40.93 USD. The simulation results demonstrate that MPSO-EO has fairly good performance for solving the UCP with significant total operating cost savings compared to standard EO compared with other reported techniques.

Optimal Control Method of Variable Air Volume Terminal Unit System

This study reviewed the existing studies on the types of variable air volume (VAV) terminal units, control and operation methods, prediction models, and sensor calibration methods. As a result of analyzing the existing research trends on the system type, characteristics, and control method of VAV terminal units studies such as theoretical verification and energy simulation were conducted to improve the existing control methods, reset the set value using a mathematical model, and add a monitoring sensor for the application of control methods. The mathematical model used in the study of VAV terminal unit control methods was used to derive set values for minimum air volume, supply temperature, ventilation requirements, and indoor comfort. The mathematical model has a limitation in collecting input information for professional knowledge and model development, and development of a building environment prediction model using a black box model is being studied. The VAV terminal unit system uses a sensor to control the device, and when an error occurs in the sensor, indoor comfort problems and energy waste occur. To solve this problem, sensor calibration techniques have been developed using statistical models, mathematical models, and Bayesian statistical models. The possibility of developing a method for calibrating the variable air volume terminal unit sensor using the prediction model was confirmed. In conclusion, the VAV terminal unit system is one of the most energy efficient systems. The energy saving potential of current VAV systems can still be improved through control methods, the use of predictive models, and sensor calibration methods.

Sanksi Pidana terhadap Penumpang yang Membawa Barang Berbahaya dalam Penerbangan

Aviation is the transportation that is chosen by many people to support their mobility and travel efficiency. In order to maintain comfort for users of aviation transportation, the operation of flights and their supervision is regulated directly by the national transportation unit system in an integrated and systematic manner. This study aims to examine the legal arrangements for passengers who carry dangerous goods on flights and reveal criminal sanctions against passengers who carry dangerous goods on flights. This study was designed using normative legal research, with a legislative and conceptual approach. The data used are sourced from primary, secondary and tertiary legal materials obtained through reading activities. Then analyzed using literature study. The results of the study reveal that legal arrangements regarding passengers carrying dangerous goods on flights are regulated in detail and firmly in Law No. 1 of 2009 concerning Aviation, Government Regulation No. 3 of 2001 concerning security and safety in flights and the sanctions given to perpetrators who carry dangerous goods are: imprisonment for 2 years and a fine of Rp. 500,000,000

Optimising Outpatient Pharmacy Staffing to Minimise Patients Queue Time using Discrete Event Simulation

Background: To remain relevant in the customer-oriented market, hospitals must pay attention to the quality of services and meet customers' expectations from admission to discharge stage. For an outpatient customer, pharmacy is the last unit visited before discharge. It is likely to influence patient satisfaction and reflect the quality of hospital's service. However, at certain hospitals, the waiting time is long. Resources need to be deployed strategically to reduce queue time. Objective: This research aims to arrange the number of staff (pharmacists and workers) in each station in the pharmacy outpatient service to minimise the queue time.Methods: A discrete simulation method is used to observe the waiting time spent at the pharmacy. The simulation run is valid and effective to test the scenario. Results: It is recommended to add more personnel for the non-compounding medicine and packaging to reduce the waiting time by 22.41%Conclusion: By adding personnel to non-compounding and packaging stations, the system performance could be improved. Cost-effectiveness analysis should be done to corroborate the finding. Keywords: Discrete Event Simulation, Hospital, Outpatient Service, Pharmacy Unit, System AnalysisBackground: To remain relevant in the customer-oriented market, hospitals must pay attention to the quality of services and meet customers' expectations from admission to discharge stage. For an outpatient customer, pharmacy is the last unit visited before discharge. It is likely to influence patient satisfaction and reflect the quality of hospital's service. However, at certain hospitals, the waiting time is long. Resources need to be deployed strategically to reduce queue time. Objective: This research aims to arrange the number of staff (pharmacists and workers) in each station in the pharmacy outpatient service to minimise the queue time.Methods: A discrete simulation method is used to observe the waiting time spent at the pharmacy. The simulation run is valid and effective to test the scenario. Results: It is recommended to add more personnel for the non-compounding medicine and packaging to reduce the waiting time by 22.41%Conclusion: By adding personnel to non-compounding and packaging stations, the system performance could be improved. Cost-effectiveness analysis should be done to corroborate the finding. Keywords:Discrete Event Simulation, Hospital, Outpatient Service, Pharmacy Unit, System Analysis