Acme
Recommending a Low-Cost Customer Service Employee Daily Assignment Schedule
University of Maryland University College
Executive Summary
Acme De Mexico’s Manager has requested assistance in developing a minimum cost daily assignment schedule for the customer service employees in their newly built store. Specifically, he wants to know the minimum total cost per day, which is the decision variable. He also wants to know the exact amount of part time and full time employees which will determine the total cost. The objective function is to minimize costs.
Acme specified a minimum number of employees required for each shift, a maximum number of employees per shift, specific shifts for full time and part time workers, and a maximum percentage of 50% of the total hours for part time employees. These constraints were input into Microsoft solver, which determined $47,800 to be the minimum employee cost per day, employing 23 fulltime workers and 45 part time workers per day.
Specific assumptions were made which will be discussed in detail, along with the impact of non-typical days. A sensitivity analysis will then be performed to determine how the percentage of part time employees’ constraint affects the total cost per day.
Introduction
Now the Acme De Mexico has completed the building process, it is now time to properly staff the store. The store manager, Mr. Rodriguez, has requested a minimum cost daily assignment schedule for the customer service employees at the new store. In order to have Acme De Mexico become a profitable business, it must make the best use of its resources (Jacobs & Chase, 2013). In this case the resources are time, money, and employees. In order to provide Mr. Rodriguez with the information he requested, linear programming will be utilized.
Linear programming is the “several related mathematical techniques used to allocate limited resources among competing demands in an optimal way” (Jacobs & Chase, 2013, appendix
University of Maryland University College
Executive Summary
Acme De Mexico’s Manager has requested assistance in developing a minimum cost daily assignment schedule for the customer service employees in their newly built store. Specifically, he wants to know the minimum total cost per day, which is the decision variable. He also wants to know the exact amount of part time and full time employees which will determine the total cost. The objective function is to minimize costs.
Acme specified a minimum number of employees required for each shift, a maximum number of employees per shift, specific shifts for full time and part time workers, and a maximum percentage of 50% of the total hours for part time employees. These constraints were input into Microsoft solver, which determined $47,800 to be the minimum employee cost per day, employing 23 fulltime workers and 45 part time workers per day.
Specific assumptions were made which will be discussed in detail, along with the impact of non-typical days. A sensitivity analysis will then be performed to determine how the percentage of part time employees’ constraint affects the total cost per day.
Introduction
Now the Acme De Mexico has completed the building process, it is now time to properly staff the store. The store manager, Mr. Rodriguez, has requested a minimum cost daily assignment schedule for the customer service employees at the new store. In order to have Acme De Mexico become a profitable business, it must make the best use of its resources (Jacobs & Chase, 2013). In this case the resources are time, money, and employees. In order to provide Mr. Rodriguez with the information he requested, linear programming will be utilized.
Linear programming is the “several related mathematical techniques used to allocate limited resources among competing demands in an optimal way” (Jacobs & Chase, 2013, appendix
References: Knode, C.S. (2011). Linear programming - Part 1 - Formulating the problem [video]. Retrieved from: http://vimeo.com/duffer44/linear-programming-part-1 Jacobs, F.R & Chase, R.B. (2013). Operations and supply management: The core, 3e. Chapter 1 and Appendix A