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The goal is then to find for some instance x an optimal solution, that is, a feasible solution y with (,) = {(, ′): ′ ()}. 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 .
Infinite-dimensional optimization studies the case when the set of feasible solutions is a subset of an infinite-dimensional space, such as a space of functions. Heuristics and metaheuristics make few or no assumptions about the problem being optimized. Usually, heuristics do not guarantee that any optimal solution need be found.
A basis B of the LP is called dual-optimal if the solution = is an optimal solution to the dual linear program, that is, it minimizes . In general, a primal-optimal basis is not necessarily dual-optimal, and a dual-optimal basis is not necessarily primal-optimal (in fact, the solution of a primal-optimal basis may even be unfeasible for the ...
B will denote the best solution found so far, and will be used as an upper bound on candidate solutions. Initialize a queue to hold a partial solution with none of the variables of the problem assigned. Loop until the queue is empty: Take a node N off the queue. If N represents a single candidate solution x and f(x) < B, then x is the best ...
Here, the best solution to instance x of problem P has a cost above c⋅k. The gap between the two thresholds is thus c. Note that whenever OPT falls between the thresholds, there is no requirement on what the output should be. A valid algorithm for the c-gap problem may answer anything if OPT is in the middle of the gap.
Multi-objective optimization or Pareto optimization (also known as multi-objective programming, vector optimization, multicriteria optimization, or multiattribute optimization) is an area of multiple-criteria decision making that is concerned with mathematical optimization problems involving more than one objective function to be optimized simultaneously.
If the follower has more than one optimal response to a certain selection of the leader, there are two possible options: either the best or the worst follower's solution with respect to the leader's objective function is assumed, i.e. the follower is assumed to act either in a cooperative way or in an aggressive way.
An optimal decision is a decision that leads to at least as good a known or expected outcome as all other available decision options. It is an important concept in decision theory . In order to compare the different decision outcomes, one commonly assigns a utility value to each of them.