Consider the resort hotel example described in problems P7 and P8 from Chapter 8. As a marketing analyst for the hotel, you can use the same data set, same cutoff points, and the same budget and cost requirements. Include multiple dimensions in your analysis

1.Formulate and solve a 0-1 LP model which uses both recency and frequency data as input. The goal of the model is to identify those hotel guest segments which maximize the expected revenue under budget limitations. These segments are defined as a combination of recency and frequency values of hotel guests who should be included in the campaign.

2.Adjust the above LP model so it identifies the percentage of hotel guests from recency and frequency segments who should be included in the campaign.

3.Focus the analysis on the recency and monetary value of stays by hotel guests. Formulate and solve a 0-1 LP model to identify the recency and monetary value segments of hotel guests who should be included in the campaign. Adjust the model to identify the percentage of hotel guests from each segment (recency and monetary value) in order to maximize the expected revenues under the same budget constraints.

4.Consider frequency and monetary value as the basis of your analysis. Formulate and solve a 0-1 LP model to identify the frequency and monetary value segments of hotel guests who should be included in the campaign in order to maximize the expected revenues under the same budget constraints. Also, adjust the model to identify the percentage of hotel guests in each of the two segments.

5.Compare the results from the three two-dimensional binary LP models. Generate insights and recommendations for the hotel management regarding the future of marketing campaigns and segments of hotel guests which should be reached in order to maximize the expected revenues.