Analysis using queue model equations

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Reference no: EM132091890

Assignment 1 – The Airline Ticket Desk CREATE 1 PAGE EXECUTIVE SUMMARY on the following:

Chalk airlines needs your help in determining if they will experience long wait lines when they open up a new satellite office in North Miami Beach, Florida next year.

Question: based on the information in the case study…Write a one page Executive Summary.

The Executive Summary should include:

-analysis using queue model equations, and

-your recommendation to manage wait lines.

Case Study

Chalk's International Airlines, formerly Chalk's Ocean Airways, was an airline with its headquarters on the grounds of Fort Lauderdale-Hollywood International Airport in unincorporated Broward County, Florida near Fort Lauderdale. It operated scheduled seaplane services to the Bahamas. Its main base was Miami Seaplane Base (MPB) until 2001, with a hub at Fort Lauderdale-Hollywood International Airport.

The airline was founded by Arthur "Pappy" Chalk, and started ad-hoc charter operations as the Red Arrow Flying Service in 1917. After "Pappy" Chalk served in the Army Air Service in World War I, he returned to Miami and commenced scheduled service between Miami and Bimini in the Bahamas in February 1919 as Chalk's Flying Service. Chalk's first base was a beach umbrella on the Miami shore of Biscayne Bay. In 1926 a landfill island, Watson Island, was created in Biscayne Bay close to Miami. Chalk's built an air terminal there, and operated from the island for the next 75 years.

Pappy Chalk sold the airline to a friend in 1966,but continued to be involved in the daily operations of the airline until he retired in 1975. He died in 1977 at the age of 88.

Chalk's Ocean Airways is planning to open a satellite ticket desk in a new shopping plaza, staffed by one ticket agent. It is estimated that request for tickets and information will average 18 per hour, and request will have a Poisson distribution. Previous experience with similar satellite operations suggest that mean services time should average about three minutes per request. Determine each of the following:

-System utilization

-Percentage of time the server (agent) will be idle.

-Average time spent in the system.

-Average number of customers in the system

-Average number of customers in the queue

-Average time a customer is in the queue

-The probability of zero customers in the system and the probability of four customers.

Reference no: EM132091890

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