feasible schedule - meaning and definition. What is feasible schedule
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What (who) is feasible schedule - definition

SET OF ALL POSSIBLE POINTS OF AN OPTIMIZATION PROBLEM THAT SATISFY THE PROBLEM'S CONSTRAINTS
Feasible set; Candidate solution; Candidate solutions; Feasible solution; Feasible set (optimization); Solution space; Solution Space
  • A closed feasible region of a [[linear programming]] problem with three variables is a convex [[polyhedron]].
  • A problem with five linear constraints (in blue, including the non-negativity constraints). In the absence of integer constraints the feasible set is the entire region bounded by blue, but with [[integer constraint]]s it is the set of red dots.

Feasible region         
In mathematical optimization, a feasible region, feasible set, search space, or solution space is the set of all possible points (sets of values of the choice variables) of an optimization problem that satisfy the problem's constraints, potentially including inequalities, equalities, and integer constraints. This is the initial set of candidate solutions to the problem, before the set of candidates has been narrowed down.
Vaccination schedule         
  • access-date=5 March 2020}}</ref>
SERIES OF VACCINATIONS
Adult Immunization; Vaccine schedule; Immunization schedule; Vaccination program; Neonate vaccination; US vaccination program; US vaccination schedule; Vaccine program; Child vaccination; Baby vaccinations; Routine immunizations; Routine vaccinations; Routinely vaccinate; Routine immunization; Vaccination Schedule
A vaccination schedule is a series of vaccinations, including the timing of all doses, which may be either recommended or compulsory, depending on the country of residence.
FastTrack Schedule         
SOFTWARE
Fasttrack schedule
FastTrack Schedule is a project management software program that is used for planning, tracking, and reporting project goals. Available since 1987, it is made by AEC Software, Inc.

Wikipedia

Feasible region

In mathematical optimization, a feasible region, feasible set, search space, or solution space is the set of all possible points (sets of values of the choice variables) of an optimization problem that satisfy the problem's constraints, potentially including inequalities, equalities, and integer constraints. This is the initial set of candidate solutions to the problem, before the set of candidates has been narrowed down.

For example, consider the problem of minimizing the function x 2 + y 4 {\displaystyle x^{2}+y^{4}} with respect to the variables x {\displaystyle x} and y , {\displaystyle y,} subject to 1 x 10 {\displaystyle 1\leq x\leq 10} and 5 y 12. {\displaystyle 5\leq y\leq 12.\,} Here the feasible set is the set of pairs (x, y) in which the value of x is at least 1 and at most 10 and the value of y is at least 5 and at most 12. The feasible set of the problem is separate from the objective function, which states the criterion to be optimized and which in the above example is x 2 + y 4 . {\displaystyle x^{2}+y^{4}.}

In many problems, the feasible set reflects a constraint that one or more variables must be non-negative. In pure integer programming problems, the feasible set is the set of integers (or some subset thereof). In linear programming problems, the feasible set is a convex polytope: a region in multidimensional space whose boundaries are formed by hyperplanes and whose corners are vertices.

Constraint satisfaction is the process of finding a point in the feasible region.