Final answer:
Without the specific LP problem details, it's not possible to solve for the second tableau or find the optimal solution. However, the simplex method involves pivot operations that iteratively improve the objective function while maintaining feasibility.
Step-by-step explanation:
To solve the given LP problem by using the simplex method, one has to follow a systematic process of converting the constraints into equations, identifying the basic and non-basic variables, initializing the simplex tableau, performing pivot operations, and checking for optimality conditions. The goal is to maximize or minimize the objective function while adhering to the constraints.
Unfortunately, the actual LP problem is not provided; however, given typical steps involved in the simplex method, after setting up the initial simplex tableau and identifying the initial basic variables (which are usually the slack variables), pivot operations are performed. These pivots involve choosing a entering variable from the non-basic variables and a leaving variable from the current set of basic variables, to improve the objective function value.
Without the specific problem, we can't solve for the basic variables at the second tableau or provide an optimal solution. Nevertheless, the typical options given for multiple-choice questions consist of a set of basic variable values and the corresponding values for the decision variables (usually X¹, X²) that maximize or minimize the objective function Z.