JUST PART ONE PLEASE

A small company named Log Transit has at present 3 manufacturing facilities (suppliers) called Sappliers $1, #2, and #3 to sapply goods to its 3 retail stores (customers) named Castomer A, B, and C. Due to eustomer dernands at stores increasing. the company docided to baild a new manafacturing facility (Supplier) that will have a capacity of 200 units per week. Afier screening many potential sites for the new facility, Toledo and Cincinnati have been determinod to be the two leading candidate locations. Assume that from Suppliers to Custorners will be the main determinant to determine which of the two locations to be selected as the new plant site. The following two tables provide information on i) the capacities of old suppliers and new supplier eandidates; ii) The per unit Transportation cost from existing Suppliers to customers and per unit Transportation cost from the new eandidate supplier location to customers, and 3) demands from customers and available capacity of each supplier. One of the most important tasks of this project is to determine which New Supplier locations will result in the smallest total transportation costs. The following is what you need to do to complete this project Part 1: L.P formulation a. Give a surnmary of the project Problem: - Describe in WORDS what Decision you need to make, and criterion on which your decision is based, and how Linear Programming models can be used to help you make your decision. b. Formulate the project problem into TWO L.P models. - To make the right decision for the project, you need to formulate TWO Linear Programming models. - You may only provide a complete and detailed L.P formulation for only one of the models. For example, assuming "TOLEDO" is chosen as the new plant. Then, give brief explanations of the difference in LP model formulation when "CWNCNNATT" is chosen as the new plant. c. Gimportane A Linear Programming Model formulation should be a Mathematical Model that contains - Clearly defined decision variables - A linear function of the Objective - All constraints in the form of Linear inequalities/equalities for which your decision variables need io satisfy, including non-negativity constraints