Knowledge that Transforms

The generalized linear programming algorithm allows an arbitrary mathematical programming minimization problem to be analyzed as a sequence of linear programming approximations. Under fairly general assumptions, it is demonstrated that any limit point of the sequence of optimal linear programming dual prices produced by the algorithm is optimal in a concave maximization problem that is dual to the arbitrary primal problem. This result holds even if the generalized linear programming problem does not solve the primal problem. The result is a consequence of the equivalence that exists between the operations of convexification and dualization of a primal problem. The exact mathematical nature of this equivalence is given.

This note points out an omission in L. S. White [White, L. S. 1969. Shortest route models for allocation of inspection effort on a production line. Management Sci. 15 249–259.]. It also suggests a modification in the problem formulation.

Given a group composed of N individuals and given that each has rated all of the alternatives using a cardinal utility function, the problem is to aggregate these to obtain a group cardinal utility function for evaluating each alternative. The cardinal utilities indicate the strength of preference of one alternative relative to others as well as order the alternatives. Five assumptions, which seem reasonable for the aggregation, are postulated, and it is shown the group cardinal utility function which is implied must be a linear combination of the individual cardinal utility functions. For assessing such a function, interpersonal comparisons of preferences are required. Suggestions for who should make these comparisons and how they might be done are given.

Why are over 2,000 corporations either using, developing, or planning to develop some form of corporate simulation model? What types of companies are using corporate planning models? How are they being used? Which resources are required? These are among the questions which were raised in a recent survey of 346 companies whose results are summarized in this paper. The paper also examines the costs and benefits to be derived from using corporate simulation models. Finally, drawing on the survey results, the authors speculate on future developments in the field of corporate modeling.

This paper presents a network model for the analysis of waste management systems. In the “waste management network” that we develop waste-generating activities correspond to sources, each node corresponds to a specific flow (waste) form, and each arc to a flow transformation; a chain from a source to a destination represents in turn waste generation, treatment, and disposal, while a feasible flow pattern constitutes a possible waste management system. The model resembles the maximal multi-commodity flow model with positive gains (single transformation) along the arcs, but in addition it admits multi-transformations, interrelations among arc flows, and flow-dependent budget restrictions. The problem is formulated as a linear program where each column in the constraint matrix corresponds to a chain in the network. The solution procedure uses a column-generation scheme based on a shortest route algorithm adapted for multi-transformed flows. Recycling, discharge and effluent standards, charges, damage costs and various budgeting schemes can be handled. An illustrative hypothetical example is given.