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a) General similarities between dynamic programming and linear programming:

Dynamic programming and linear programming are both mathematical optimization techniques used to solve complex problems in various fields such as engineering, economics, and computer science. Both techniques involve formulating a mathematical model to represent the problem, defining an objective function to optimize, and setting constraints to limit the solution space. Both techniques aim to find an optimal solution that maximizes or minimizes the objective function while satisfying the constraints. Both techniques require the use of iterative algorithms to find the optimal solution. Finally, both techniques can be used to solve problems that involve a large number of variables.

b) How dynamic programming differs conceptually from linear programming:

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