Mixed-Integer Linear Programming Algorithm for a Computational Protein Design Problem

2007 ◽  
Vol 46 (3) ◽  
pp. 839-845 ◽  
Author(s):  
Yushan Zhu
1982 ◽  
Vol 104 (4) ◽  
pp. 837-843
Author(s):  
T. F. Conry ◽  
J. A. Werhane

The optimum design problem is formulated for the selection of pipe sizes in a hydraulic network such as a power plant service water or bearing cooling water system. The flows in each branch of the network are taken to be known, which makes the design problem linear in the variables. The optimization problem is formulated as a mixed integer linear programming problem. A design example is given. The role of this problem formulation and solution method in an interactive computer aided design (CAD) system is discussed.


1993 ◽  
Vol 70 (1) ◽  
pp. 27-35 ◽  
Author(s):  
David Sklan ◽  
Ilana Dariel

Human diet planning is generally carried out by selecting the food items or groups of food items to be used in the diet and then calculating the composition. If nutrient quantities do not reach the desired nutritional requirements, foods are exchanged or quantities altered and the composition recalculated. Iterations are repeated until a suitable diet is obtained. This procedure is cumbersome and slow and often leads to compromises in composition of the final diets. A computerized model, planning diets for humans at minimum cost while supplying all nutritional requirements, maintaining nutrient relationships and preserving eating practices is presented. This is based on a mixed-integer linear-programming algorithm. Linear equations were prepared for each nutritional requirement. To produce linear equations for relationships between nutrients, linear transformations were performed. Logical definitions for interactions such as the frequency of use of foods, relationships between exchange groups and the energy content of different meals were defined, and linear equations for these associations were written. Food items generally eaten in whole units were defined as integers. The use of this program is demonstrated for planning diets using a large selection of basic foods and for clinical situations where nutritional intervention is desirable. The system presented begins from a definition of the nutritional requirements and then plans the foods accordingly, and at minimum cost. This provides an accurate, efficient and versatile method of diet formulation.


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