linear Programming to Improve Raw Coal Blending: A New Twist to an Old Tool

G. T. Lineberry; E. L. Gillenwater

doi:10.1080/07349348708945534

linear Programming to Improve Raw Coal Blending: A New Twist to an Old Tool

G. T. Lineberry, E. L. Gillenwater

Research output: Contribution to journal › Article › peer-review

7 Scopus citations

Abstract

A traditional linear programming technique is offered to optimize raw coal blending for a given plant with known performance characteristics. The model matches raw coal feed rates to a plant's assumed optimum “target” feed, subject to quality and quantity constraints. The technique’s usefulness is enhanced by a novel computer program for optimizing clean coal sampling frequency. This program analyzes a plant’s current sampling scheme, models alternatives, and compares results. The user is presented a menu of feasible sampling schemes which can improve plant economics significantly. Adoption of these improved sampling programs provides the plant operator with a clearer view of the cleaning potential of the plant, permitting tighter quality control of clean coal output.

Original language	English
Pages (from-to)	227-239
Number of pages	13
Journal	Coal Preparation
Volume	4
Issue number	3-4
DOIs	https://doi.org/10.1080/07349348708945534
State	Published - Jun 1 1987

Bibliographical note

Funding Information:
Work was performed under a granl provided bythe Institute for Mining and Minerals Research, Lexington, Kentucky, through Mining and Minerals Resources Research Institute Grant No. GI134121, for the V.S. Bureau of Mines, Department of Interior.

ASJC Scopus subject areas

Fuel Technology
Geotechnical Engineering and Engineering Geology

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title = "linear Programming to Improve Raw Coal Blending: A New Twist to an Old Tool",

abstract = "A traditional linear programming technique is offered to optimize raw coal blending for a given plant with known performance characteristics. The model matches raw coal feed rates to a plant's assumed optimum “target” feed, subject to quality and quantity constraints. The technique{\textquoteright}s usefulness is enhanced by a novel computer program for optimizing clean coal sampling frequency. This program analyzes a plant{\textquoteright}s current sampling scheme, models alternatives, and compares results. The user is presented a menu of feasible sampling schemes which can improve plant economics significantly. Adoption of these improved sampling programs provides the plant operator with a clearer view of the cleaning potential of the plant, permitting tighter quality control of clean coal output.",

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N2 - A traditional linear programming technique is offered to optimize raw coal blending for a given plant with known performance characteristics. The model matches raw coal feed rates to a plant's assumed optimum “target” feed, subject to quality and quantity constraints. The technique’s usefulness is enhanced by a novel computer program for optimizing clean coal sampling frequency. This program analyzes a plant’s current sampling scheme, models alternatives, and compares results. The user is presented a menu of feasible sampling schemes which can improve plant economics significantly. Adoption of these improved sampling programs provides the plant operator with a clearer view of the cleaning potential of the plant, permitting tighter quality control of clean coal output.

AB - A traditional linear programming technique is offered to optimize raw coal blending for a given plant with known performance characteristics. The model matches raw coal feed rates to a plant's assumed optimum “target” feed, subject to quality and quantity constraints. The technique’s usefulness is enhanced by a novel computer program for optimizing clean coal sampling frequency. This program analyzes a plant’s current sampling scheme, models alternatives, and compares results. The user is presented a menu of feasible sampling schemes which can improve plant economics significantly. Adoption of these improved sampling programs provides the plant operator with a clearer view of the cleaning potential of the plant, permitting tighter quality control of clean coal output.

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linear Programming to Improve Raw Coal Blending: A New Twist to an Old Tool

Abstract

Bibliographical note

ASJC Scopus subject areas

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