2018
DOI: 10.1016/j.simpat.2017.10.004
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Simulation modeling of Houston Ship Channel vessel traffic for optimal closure scheduling

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Cited by 31 publications
(11 citation statements)
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“…It is briefly said that the genetic algorithm is a programming technique that uses genetic evolution as a problem-solving model. This is an evolutionary search algorithm to find an approximated optimal solution starting with a set of the initial solution [25][26][27][28]. The input of this program is a problem that needs to be solved and solutions are coded according to a template.…”
Section: Genetic Algorithmmentioning
confidence: 99%
“…It is briefly said that the genetic algorithm is a programming technique that uses genetic evolution as a problem-solving model. This is an evolutionary search algorithm to find an approximated optimal solution starting with a set of the initial solution [25][26][27][28]. The input of this program is a problem that needs to be solved and solutions are coded according to a template.…”
Section: Genetic Algorithmmentioning
confidence: 99%
“…Simulation models of the vessel traffic on the specific canal sections in function of the waterway capacity are developed according to the type of the technological process of vessel traffic on observed real section -two-way section ld=35000 m and one-way section lj=8030 m [17]. Simulation experiments are performed for various cases of vessel traffic densities, under constant basic parameters (vessel length L=77 m; navigation speed v=8 km/h; period duration t=30 days; vessels arrivals correspond to Poisson's distribution [10], FIFO/FCFS queue priority). For models with timesequential regulation of entrances, four cycle durations were used -30, 60, 120 and 240 minutes.…”
Section: Capacity Of the One-way Section Of Waterwaymentioning
confidence: 99%
“…The study compared the proposed schedule with the schedules formerly applied and presented notable similarities. Rahimikelarijani et al (2018) considered the effects of closing the Houston Channel (to construct a bridge) for several alternative time slots. The study used statistical tools such as ANOVA and determined the best slot that minimised vessel waiting times.…”
Section: Introductionmentioning
confidence: 99%