(25 points) Linearize the quadratic assignment formulation for Quadratic Assignment Formulation of the TSP There are an enormous number of subtour elmination constraints for a TSP on even a modest number of points. That is why it is sometimes easier-especially in developing heuristic procedures of Chapter 15to deal with a TSP formulation having simpler constraints. We can accomplish this, at the cost of making the objective function non- linear, by formulating the TSP as a quadratic assignment (QAP) model 11.16. Think of the tour as a sequence or permutation of the points to be visited. Decision variables in the OAP form assign sequence positions k to points is that is. fi if kth point visited is i 10 otherwise For example, the illustrative route of Figure 11.4 has V1.1 - Y23 F Y36 = 745 = Y5.4 = 76.8 179 18,10 V9,7 = V10.2 1 when viewed as starting at hole 1. In terms of these variables, either the symmetric or the asymmetric case can be formulated as an INLP. Give the full linearized model. (25 points) Linearize the quadratic assignment formulation for Quadratic Assignment Formulation of the TSP There are an enormous number of subtour elmination constraints for a TSP on even a modest number of points. That is why it is sometimes easier-especially in developing heuristic procedures of Chapter 15to deal with a TSP formulation having simpler constraints. We can accomplish this, at the cost of making the objective function non- linear, by formulating the TSP as a quadratic assignment (QAP) model 11.16. Think of the tour as a sequence or permutation of the points to be visited. Decision variables in the OAP form assign sequence positions k to points is that is. fi if kth point visited is i 10 otherwise For example, the illustrative route of Figure 11.4 has V1.1 - Y23 F Y36 = 745 = Y5.4 = 76.8 179 18,10 V9,7 = V10.2 1 when viewed as starting at hole 1. In terms of these variables, either the symmetric or the asymmetric case can be formulated as an INLP. Give the full linearized model