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How do you calcualte the optimal size of IPO?
How do you calculate the optimal size of an IPO?
What is the difference between optimal and optimum?
They are synonyms, which means they mean the same thing, so you can use either; it makes no difference. However, "optimal" can be made into an adverb, "optimally", but "optimum" cannot. Both can function as an adjective but only "optimum" can be used as a noun. In fact, there are some people who believe that "optimum" should only be used as a noun and it's only because people have repeatedly used it as an adjective (incorrectly) over a long period of time that it has become acceptable as an adjective. So if you want to be safe, it would be best to only use "optimum" as a noun. But I'm sure no one would correct you if you used it as an adjective, especially because all dictionaries I've looked at list it as both.
What is the difference between thousand barrels per calendar day mbcd and thousands barrels per operating day mbod?
Barrels per calendar day: The amount of input that a distillation facility can process under usual operating conditions. The amount is expressed in terms of capacity during a 24-hour period and reduces the maximum processing capability of all units at the facility under continuous operation to account for the following limitations that may delay, interrupt, or slow down production. 1. the capability of downstream processing units to absorb the output of crude oil processing facilities of a given refinery. No reduction is necessary for intermediate streams that are distributed to other than downstream facilities as part of a refinery's normal operation; 2. the types and grades of inputs to be processed; 3. the types and grades of products expected to be manufactured; 4. the environmental constraints associated with refinery operations; 5. the reduction of capacity for scheduled downtime due to such conditions as routine inspection, maintenance, repairs, and turnaround; and 6. the reduction of capacity for unscheduled downtime due to such conditions as mechanical problems, repairs, and slowdowns.Barrels per stream day: The maximum number of barrels of input that a distillation facility can process within a 24-hour period when running at full capacity under optimal crude and product slate conditions with no allowance for downtime.From U.S. Energy Information Administration
What viscosty is the rearend fluid on 3500 chev?
The recommended viscosity for the rear end fluid in a 3500 Chevrolet truck typically is 75W-90 or 75W-140, depending on the specific differential type and operating conditions. It's important to consult the owner's manual or a service guide for your specific model year to ensure the correct fluid is used. Always use a high-quality gear oil that meets or exceeds GM specifications for optimal performance.
What is Lagrange-multipliers?
Lagrange multipliers is a mathematical method used to find the local maxima and minima of a function subject to equality constraints. It introduces additional variables, called Lagrange multipliers, which help incorporate the constraints into the optimization problem. By solving the system of equations formed by the gradients of the objective function and the constraints, one can identify optimal solutions while respecting the given conditions. This technique is widely used in various fields, including economics, engineering, and physics.
State the difference between a feasible solution basic feasible solution and an optimal solution of a lpp?
the optimal solution is best of feasible solution.this is as simple as it seems
What is the difference between feasible solution and basic feasible solution?
optimal solution is the possible solution that we able to do something and feasible solution is the solution in which we can achieve best way of the solution
Why optimal solution is only at corner point?
feasible region gives a solution but not necessarily optimal . All the values more/better than optimal will lie beyond the feasible .So, there is a good chance that the optimal value will be on a corner point
What is optimal solution?
It is usually the answer in linear programming. The objective of linear programming is to find the optimum solution (maximum or minimum) of an objective function under a number of linear constraints. The constraints should generate a feasible region: a region in which all the constraints are satisfied. The optimal feasible solution is a solution that lies in this region and also optimises the obective function.
What is the difference between greedy algorithm and Divide and Conquer?
greedy method does not give best solution always.but divide and conquer gives the best optimal solution only(for example:quick sort is the best sort).greedy method gives feasible solutions,they need not be optimal at all.divide and conquer and dynamic programming are techniques.
What is optimal feasible solution?
It is usually the answer in linear programming. The objective of linear programming is to find the optimum solution (maximum or minimum) of an objective function under a number of linear constraints. The constraints should generate a feasible region: a region in which all the constraints are satisfied. The optimal feasible solution is a solution that lies in this region and also optimises the obective function.
Is (-12) a one solution?
A solution is Pareto optimal if there exists no feasible solution for which an improvement in one objective does not lead to a simultaneous degradation in one (or more) of the other objectives. That solution is a nondominated solution.
Non-degenerate basic feasible solution?
A non-degenerate basic feasible solution in linear programming is one where at least one of the basic variables is strictly positive. In contrast to degenerate solutions where basic variables might be zero, non-degenerate solutions can help optimize algorithms as they ensure progress in the search for the optimal solution.
What is the strong duality proof for linear programming problems?
The strong duality proof for linear programming problems states that if a linear programming problem has a feasible solution, then its dual problem also has a feasible solution, and the optimal values of both problems are equal. This proof helps to show the relationship between the primal and dual problems in linear programming.
Is it possible for an linear programming model to have exact two optimal solutions?
Yes, but only if the solution must be integral. There is a segment of a straight line joining the two optimal solutions. Since the two solutions are in the feasible region part of that line must lie inside the convex simplex. Therefore any solution on the straight line joining the two optimal solutions would also be an optimal solution.
Is Feasible region is necessary to be a convex set?
Yes, in optimization problems, the feasible region must be a convex set to ensure that the objective function has a unique optimal solution. This is because convex sets have certain properties that guarantee the existence of a single optimum within the feasible region.
What is the difference between simplex and dual simplex problem?
The simplex method is an algorithm used to solve linear programming problems, typically starting from a feasible solution and moving toward optimality by improving the objective function. In contrast, the dual simplex method begins with a feasible solution to the dual problem and iteratively adjusts the primal solution to maintain feasibility while improving the objective. The dual simplex is particularly useful when the primal solution is altered due to changes in constraints, allowing for efficient updates without reverting to a complete re-solution. Both methods ultimately aim to find the optimal solution but operate from different starting points and conditions.
