This paper presents a discrete-event simulation (DES) study on road traffic intersections at one of the fastest developing towns in Kedah, Malaysia. Inefficient traffic light control (TLC) of the existing system contributes to the road traffic congestion (RTC) especially during peak hours, which leads to environment pollution. With the increasing awareness about environmental issues, businesses and governments increasingly want to reduce the pollution which leads to green supply chain. RTC can be caused by a temporary obstruction or a permanent capacity bottleneck in the network itself. A DES model was developed based on current system and then “what-if” scenario was analyzed to check whether improvement would be achieved. Results from the analysis show that average waiting time and number in queue could be reduced specifically at two of the lanes under study.

One of the most prevalent and traditional uses of statistics in hydrology is flood frequency analysis. The flood can occur practically everywhere and is considered the leading cause of natural disaster death worldwide. This study aims to apply the flood frequency analysis of the Kelantan streamflow site to identify the optimal distribution that best fits the flood frequency data from the goodness-of-fit test (GOF). Five distributions were applied in this study; namely lognormal (LG), generalized extreme value (GEV), generalized Pareto (GP), log-Pearson three (L3) and generalized logistic (GL) distribution. to obtain the parameter estimates. The distribution performance evaluation is then performed utilizing the GOF and efficiency evaluations. The results indicate that the generalized GP distribution is the best possible function for determining the annual peak flow at the Kelantan streamflow site.

With the growing number of vehicles on the road, traffic flow problems are no longer a local issue; instead, traffic flow optimization has drawn significant interest from researchers all over the world. Studies of discrete-event simulation have been widely used to encounter problems related to traffic flow. Researchers of discrete-event simulation modeling typically tend to use statistical distributions for inter-arrival and process times based on the simulation software's built-in tools. The software tools include Input Analyzer in Arena, Stat::Fit for Promodel, and ExpertFit for FlexSim. However, there are other numerical metrics and concerns that researchers should examine while deciding on the best distribution. This research explores the exponential distribution and compares it to distributions generated by software, then to real data. The square error value is the focus of the comparison. There were 5404 data points collected for the vehicle arriving at six lanes at selected traffic junctions. According to the findings of this study, the commonly used exponential distribution can be utilized to depict the distribution of inter-arrival times as there is no significant difference from the more complex distribution. In future study, researcher can comfortably use exponential distribution instead of using complex distribution.

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