What is a cutter stock used for?
Cutter stock is any stream that is blended to reduce the viscosity of the resulting blend. Cutter stock is commonly used in fuel oil blending. Fuel oil tends to be a sink for high-viscosity resid that must be offset by blending lower-viscosity material to meet the viscosity specification of the fuel oil.
What does CUTR stand for?
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What is the difference between Cutter Stock and fuel oil?
These cutter stocks are significantly more valuable than the resulting fuel oil blend, so this loss of value translates into a significant cost of meeting the viscosity specification of the fuel oil. Therefore, refiners look for all ways possible to minimize the amount of cutter stock in the finished blend while still producing on-spec fuel oil.
What is the cutting stock problem?
The cutting stock problem of determining, for the one-dimensional case, the best master size that will meet given demand is known as the assortment problem. The cutting stock problem was first formulated by Kantorovich in 1939.
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HIGH-QUALITY BLENDING AND TRADING
Cutter stocks are another specialism of Orim Energy. Our industry experts have decades of experience and an excellent track record in cutter stock trading. As a result, we have in-depth market knowledge and long-term relationships with our business partners.
Why cutter stocks?
Cutter stocks are oil and oil-related (by)products used to thin oil. They are typically used to reduce viscosity to produce on-spec European fuel oils. But they can also be blended to reduce sulphur content and produce low sulphur fuel oils.
Our Cutter Stocks
We collect our cutter stocks from Northwest Europe: clean bulk cutter stocks for blending by barges and other cutter products from the petrochemical and chemical industry arriving by truck. For reception and storage, we use our tank terminal in the Rotterdam and Antwerp area.
What is the cutting stock problem?
In operations research, the cutting-stock problem is the problem of cutting standard-sized pieces of stock material, such as paper rolls or sheet metal, into pieces of specified sizes while minimizing material wasted.
Why is cutting stock degenerate?
This degeneracy arises because it is possible to move items around, creating new patterns, without affecting the amount of waste.
Who first proposed the cutting stock problem?
The cutting stock problem was first formulated by Kantorovich in 1939. In 1951 before computers became widely available, L. V. Kantorovich and V. A. Zalgaller suggested solving the problem of the economical use of material at the cutting stage with the help of linear programming.
When is Cutera's next conference?
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Is Cutera a Japanese company?
(NASDAQ: CUTR) ("Cutera" or the "Company"), a leading provider of laser and other energy-based aesthetic systems for practitioners worldwide, today announced that it has renewed its agreement with ZO Skin Health to be the exclusive distributor of ZO’s skincare products in Japan. The initial term of the new agreement spans three years from the effective date of June 15, 2021, with annual renewal options for Cutera in each of the two years following the
Is Cutera a big mover?
Cutera (CUTR) was a big mover last session on higher-than-average trading volume. The latest trend in earnings estimate revisions might help the stock continue moving higher in the near term.
Overview
In operations research, the cutting-stock problem is the problem of cutting standard-sized pieces of stock material, such as paper rolls or sheet metal, into pieces of specified sizes while minimizing material wasted. It is an optimization problem in mathematics that arises from applications in industry. In terms of computational complexity, the problem is an NP-hard problem reducible to the knapsack problem. The problem can be formulated as an integer linear programming problem.
Illustration of one-dimensional cutting-stock problem
A paper machine can produce an unlimited number of master (jumbo) rolls, each 5600 mm wide. The following 13 items must be cut, in the table below.
The important thing about this kind of problem is that many different product units can be made from the same master roll, and the number of possible combinations is itself very large, in general, and not trivial to enumerate.
Classification
Cutting-stock problems can be classified in several ways. One way is the dimensionality of the cutting: the above example illustrates a one-dimensional (1D) problem; other industrial applications of 1D occur when cutting pipes, cables, and steel bars. Two-dimensional (2D) problems are encountered in furniture, clothing and glass production. When either the master item or the required parts are irregular-shaped (a situation often encountered in the leather, textile, m…
Applications
Industrial applications of cutting-stock problems for high production volumes arise especially when basic material is produced in large rolls that are further cut into smaller units (see roll slitting). This is done e.g. in paper and plastic film industries but also in production of flat metals like steel or brass. There are many variants and additional constraints arising from special production cons…
History
The cutting stock problem was first formulated by Kantorovich in 1939. In 1951 before computers became widely available, L. V. Kantorovich and V. A. Zalgaller suggested solving the problem of the economical use of material at the cutting stage with the help of linear programming. The proposed technique was later called the column generation method.
Mathematical formulation and solution approaches
The standard formulation for the cutting-stock problem (but not the only one) starts with a list of m orders, each requiring pieces, where . We then construct a list of all possible combinations of cuts (often called "patterns" or "configurations"). Let be the number of those patterns. We associate with each pattern a positive integer variable , representing how many times pattern is to be used, where . The linear integer program is then:
See also
• High-multiplicity bin packing
• Configuration linear program
Further reading
• Chvátal, V. (1983). Linear Programming. W.H. Freeman. ISBN 978-0-7167-1587-0.
• Hatem Ben Amor, J.M. Valério de Carvalho, Cutting Stock Problems in Column Generation, edited by Guy Desaulniers, Jacques Desrosiers, and Marius M. Solomon, Springer, 2005, XVI, ISBN 0-387-25485-4
• M. Delorme, M. Iori, S. Martello, Bin packing and cutting stock problems: Mathematical models and exact algorithms, European Journal of Operational Research 2016, 255, 1–20,
• Chvátal, V. (1983). Linear Programming. W.H. Freeman. ISBN 978-0-7167-1587-0.
• Hatem Ben Amor, J.M. Valério de Carvalho, Cutting Stock Problems in Column Generation, edited by Guy Desaulniers, Jacques Desrosiers, and Marius M. Solomon, Springer, 2005, XVI, ISBN 0-387-25485-4
• M. Delorme, M. Iori, S. Martello, Bin packing and cutting stock problems: Mathematical models and exact algorithms, European Journal of Operational Research 2016, 255, 1–20, doi:10.1016/j.…