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The maximization of producer surplus can in some cases reduce consumer surplus. [15] Some forms of producer profit maximization are considered anti-competitive practices and are regulated by competition law. [15] Maximization of short-term producer profit can reduce long-term producer profit, which can be exploited by predatory pricing such as ...
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 ...
For example, the inputs could be design parameters for a motor, the output could be the power consumption. For another optimization, the inputs could be business choices and the output could be the profit obtained. An optimization problem, (in this case a minimization problem), can be represented in the following way:
For example, in economics the optimal profit to a player is calculated subject to a constrained space of actions, where a Lagrange multiplier is the change in the optimal value of the objective function (profit) due to the relaxation of a given constraint (e.g. through a change in income); in such a context is the marginal cost of the ...
In general, a lexmaxmin optimization problem may have more than one optimal solution. If and are two optimal solutions, then their ordered value vector must be the same, that is, [] = [] for all [], [5]: Thm.2 that is, the smallest value is the same, the second-smallest value is the same, and so on.
This reduces the problem to a balanced assignment problem, which can then be solved in the usual way and still give the best solution to the problem. Similar adjustments can be done in order to allow more tasks than agents, tasks to which multiple agents must be assigned (for instance, a group of more customers than will fit in one taxi), or ...
The satisfiability problem, also called the feasibility problem, is just the problem of finding any feasible solution at all without regard to objective value. This can be regarded as the special case of mathematical optimization where the objective value is the same for every solution, and thus any solution is optimal.
For each combinatorial optimization problem, there is a corresponding decision problem that asks whether there is a feasible solution for some particular measure m 0. For example, if there is a graph G which contains vertices u and v, an optimization problem might be "find a path from u to v that uses the fewest edges". This problem might have ...