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Profit maximization using the total revenue and total cost curves of a perfect competitor. To obtain the profit maximizing output quantity, we start by recognizing that profit is equal to total revenue minus total cost (). Given a table of costs and revenues at each quantity, we can either compute equations or plot the data directly on a graph.
For profit maximization problems, the function can be any one-to-one mapping from elements of an optimal solution to elements of the algorithm's output. For cost minimization problems, the function can be any one-to-one mapping from elements of the algorithm's output to elements of an optimal solution.
This is a corner solution as the highest possible IC (IC 2) intersects the budget line at one of the intercepts (x-intercept). [1] In mathematics and economics, a corner solution is a special solution to an agent's maximization problem in which the quantity of one of the arguments in the maximized function is zero. In non-technical terms, a ...
C. Robert Taylor points out that the accuracy of Hotelling's lemma is dependent on the firm maximizing profits, meaning that it is producing profit maximizing output and cost minimizing input . If a firm is not producing at these optima, then Hotelling's lemma would not hold. [2]
The assignment problem is a fundamental combinatorial optimization problem. In its most general form, the problem is as follows: The problem instance has a number of agents and a number of tasks. Any agent can be assigned to perform any task, incurring some cost that may vary depending on the agent-task assignment.
Merton's portfolio problem is a problem in continuous-time finance and in particular intertemporal portfolio choice. An investor must choose how much to consume and must allocate their wealth between stocks and a risk-free asset so as to maximize expected utility .
Finding (,) is the utility maximization problem. If u is continuous and no commodities are free of charge, then x ( p , I ) {\displaystyle x(p,I)} exists, [ 4 ] but it is not necessarily unique. If the preferences of the consumer are complete, transitive and strictly convex then the demand of the consumer contains a unique maximiser for all ...
Each such problem is the subproblem obtained by dropping a sequence of variables , …, from the original problem, along with the constraints containing them. After the problem on variables x i + 1 , … , x n {\displaystyle x_{i+1},\ldots ,x_{n}} is solved, its optimal cost can be used as an upper bound while solving the other problems,