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Queuing management systems have been applied by Model Logic over the years to solve a wide range of commercial problems in defence system manufacturing, car park layout, retail check out and call centre resource planning.

The technique employed is usually known as simulation, and is a very useful in gaining understanding of the dynamics of an operation and tracking the behaviour when various demands are placed upon it.

The common four variables in all of these situations are:

1.Arrival rates of objects and pattern
2.Process or transaction times at each workstation.
3.Resource level (number of operatives or machines at each workstation)
4.Critical path with decision points along which the objects must travel.

Once the above framework is established the queue abandonment rules consider alternative behaviours when confronted by the queue length and rate of depletion.

The interplay of all the above variables and rules determine queuing levels, work in progress, resource utilisation and service levels at different times of day.

Here are four examples of how we have used queuing theory or simulation techniques to solve real life commercial problems.

1.A defence industry contractor wished to tender for a programme of armoured vehicle manufacturing. The requirement was to establish a timetable for delivery given a complex critical path and limited resource capacity. A system was developed by Model Logic using Microsoft development tools highlighting pressure points where bottlenecks were occurring allowing extra resources to be brought in/contracted out to meet the various delivery deadlines.

2.Alternative car park layouts were evaluated on behalf of a major retailer in order to find the best layout with regard to throughput and access points. Each store was considered on its own merit as there was no one cap fits all solution.

3.When a leading high street retailer was faced with the prospect of replacing all the cash tills as they were no longer being supported by the manufacturer, they needed to understand how many tills were actually needed by each department, would till banks be appropriate with a single queue, and what would be the impact on the customer experience in the form of queuing levels. A system was developed by Model Logic using Microsoft development tools considering alternative queuing strategies between a single queue multiple till bank and multiple tills each with their own queue. The system reported queuing levels and instances at a minute by minute time grain throughout the store opening hours, given various footfall, till bank formation and transaction time parameters. Using this data, the retailer determined that a single queue with multiple tills offered the most efficient system.

4.A leading retailer wished to benchmark its call centre performance and standardise the target service levels across the group. The central service level KPI to be achieved would be measured as x % of calls to be answered within y seconds. The system developed by Model Logic using the standard Microsoft tools reported the operator numbers by hour of the day required to achieve the KPI standard, given the number of incoming calls, their length, and abandonment rate. The model uses simulation techniques, but also tracks in parallel a formulaic approach developed by AK Erlang in the early 20th century. The two approaches can then be compared to double check the findings.

In each of the cases highlighted above, the throughput or objects being processed are randomly generated by the model at the specified rate. Alternatively, they could just as easily be generated from a user input schedule – depending how much control the end user wishes to place on the model.