INTEGER PROGRAMMING AND PRICING

In this article Gomory's method of solution of integer linear programming problems is described briefly (with an example of the method of solution). The bulk of the paper is devoted to a discussion of the dual prices and their relationship to the marginal yields of scarce indivisible resources and their efficient allocation. IT HAS been known for some time that a method of solution of the general linear programming problem in which the variables are required to take integer values would also permit the solution of a considerable variety of other problems many of which are not obviously related to it.1 For example, Markowitz and Manne [13] have shown that the difficult concave (nonlinear) programming problem (e.g., a cost minimization problem in which the total cost function is shaped like a hill) can, at least in principle, be approximated as an integer program which permits the determination of a global, and not just a local minimum. Nonconvex feasible regions can also, at least in principle, be handled by integer programming. Among the economic problems which are related to integer programming are the travelling salesman problem and problems in which fixed (inescapable) costs are present. A surprisingly wide range of problems including diophantine problems and the four color map problem2 can be given an integer programming formulation. Some of these applications will be described in greater detail in section five of this paper. Recently one of the authors of this article developed a method, which he calls the method of integer forms (MIF), for solving integer programming problems. In the next section the method of solution will be described in some detail. No proof that the algorithm arrives at the optimal integer solution in a finite number of steps will be described since it is rather lengthy and is being published elsewhere (see Gomory [6] and [7]. For an alternative approach see Land and Doig [12]).