Please answer questions 1-3 and fill out the excel file, thanks!

1. Briefly describe the differences between a local optima and a global optima. Be sure to also discuss when a local optima are able to be classified as global optima. 2. Briefly describe the difference between a convex function and a concave function. Wedding Planning. The distance between two cities in the United States can be approximated by the following formula, where lats and long, are the latitude and longitude of city 1 and late and long, are the latitude and longitude of city 2: 89/(lat - lata)* + (long, long,)* Ted's daughter is getting married, and he is inviting relatives from 15 different locations in the United States. The file Wedding gives the longitude, latitude, and number of relatives in each of the 15 locations. Ted would like to find a wedding location that minimizes the demand-weighted distance, where demand is the number of relatives at each location. Assuming that the wedding can occur anywhere, find the latitude and longitude of the optimal location. (Hint: Notice that all longitude values given for this problem are negative. Make sure that you do not check the option for Make Unconstrained Variables Non-Negative in Solver.) Wedding Planning Inputs oo Location New York Maryland Virginia SC NC TN FL Ohio Wyoming CA Iowa IL Mass NJ PA latitude 40.714 39.026 37.432 32.216 35.772 35.961 27.499 39.136 43.623 34.019 41.699 41.850 42.934 40.901 39.952 longitude -74.006 -77.076 -78.657 -80.753 -78.639 -83.921 -82.575 -84.503 -110.626 -118.491 -93.047 -87.650 -70.798 -74.514 -75.164 # Relatives 43 8 2 1 12 1 6 6 1 10 7 4 1 10 2 B C D D E F G 3 I A 22 Model optimal latitude optimal longitude 23 24 Wedding Site 25 The optimal location is most likely in what state? Demand Weighted Distance Latitude Difference Squared Longitude Difference Squared Distance 26 Location 27 New York 28 Maryland 29 Virginia 30 SC 31 NC 32 TN 33 FL 34 Ohio 35 Wyoming 36 CA 37 Iowa 38 IL 39 Mass 40 NJ 41 PA 42 latitude 40.714 39.026 37.432 32.216 35.772 35.961 27.499 39.136 43.623 34.019 41.699 41.850 42.934 40.901 39.952 longitude -74.006 -77.076 -78.657 -80.753 -78.639 -83.921 -82.575 -84.503 -110.626 -118.491 -93.047 -87.650 -70.798 -74.514 -75.164 # Relatives 43 8 2 1 12 1 6 6 1 10 7 4 1 10 2 2 Total Demand Weighted Distance