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The optimal solution is the best feasible solution
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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
Why do you study calculus write its at least five applications?
Integral calculus allows you to determine area under a curve, something that in probability, statistics, and physics finds very important.Calculus is important because of some of the key concepts of integration and differentiation and the countless applications they have, but also the new ideas, and new ways of looking at things.First me have to say that "Calculus" is that branch which deals with the integral calculus e.g. calculation area under the curve and the deferential calculus that deals with the motion calculation, and that all are the part of our practical life. Calculus is deeply integrated with the physical science and such as physics and Bio science, so now we can say that it is more important in every aspects of life some of them we'll here discuss.It is found in computer science, statistics, and engineering; in economics, business, and medicine. Modern developments such as architecture, aviation, and other technologies all make use of what calculus can offer. Graph visualization are also based on that, we can easily graph the function with the help of it. Finding average of function one example is the path of an airplane. Using calculus you can calculate its average cruising altitude, velocity and acceleration.Calculus is a very versatile and valuable tool. It is a form of mathematics which was developed from algebra and geometry. It is made up of two interconnected topics, differential calculus and integral calculus. Finding the Slope of a CurveCalculus can give us a generalized method of finding the slope of a curve. The slope of a line is fairly elementary, using some basic algebra it can be found. Although when we are dealing with a curve it is a different story. Calculus allows us to find out how steeply a curve will tilt at any given time. This can be very useful in any area of study· . Calculate Complicated X-interceptsWithout an idea like the Intermediate Value Theorem it would be exceptionally hard to find or even know that a root existed in some functions. Using Newton's Method you can also calculate an irrational root to any degree of accuracy, something your calculator would not be able to tell you if it wasn't for calculus.· Visualizing GraphsUsing calculus you can practically graph any function or equation you would like. In fact you can find out the maximum and minimum values, where it increases and decreases and much more without even graphing a point, all using calculus.· A function can represent many things. One example is the path of an airplane. Using calculus you can calculate its average cruising altitude, velocity and acceleration. Same goes for a car, bus, or anything else that moves along a path. Now what would you do without a speedometer on your car?· Calculating Optimal ValuesBy using the optimization of functions in just a few steps you can answer very practical and useful questions such as: "You have square piece of cardboard, with sides 1 meter in length. Using that piece of card board, you can make a box, what are the dimensions of a box containing the maximal volume?" These types of problems are a wonderful result of what calculus can do for us.· Physics makes particular use of calculus; all concepts in classical mechanics and electromagnetism are interrelated through calculus. The mass of an object of known density, the moment of inertia of objects, as well as the total energy of an object within a conservative field can be found by the use of calculusSo at the end that branch cover a lot of area of our practical life to overcome them we'd have good knowledge of it.
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.
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 corner point solution method?
The corner point solution method is a technique used in linear programming to find the optimal solution by considering the intersection points of the constraints. It involves analyzing the extreme points or corner points of the feasible region to identify the optimal value of the objective function. This method is effective for problems with few variables and constraints.
MODI method of solving transportation problem?
The first approximation to is always integral and therefore always a feasible solution. Rather than determining a first approximation by a direct application of the simplex method it is more efficient to work with the table given below called the transportation table. The transportation algorithm is the simplex method specialized to the format of table it involves: i) finding an integral basic feasible solution ii) testing the solution for optimality iii) improving the solution, when it is not optimal iv) repeating steps (ii) and (iii) until the optimal solution is obtained.
