Knowledge that Transforms

We consider a class of algorithms which use the combined powers of branch-and-bound, dynamic programming and rudimentary divisibility arguments for solving the zero-one knapsack problem. Our main result identifies a class of instances of the problem which are difficult to solve by such algorithms. More precisely, if reading the data takes t units of time, then the time required to solve the problem grows exponentially with the square root of t.

Quantitative decision analysis techniques are applied to a particular problem of bargaining and negotiation: How should a negotiating team representing the United States prepare for an international conference on tanker safety and pollution prevention? The negotiating team had a short time to prepare for the Conference, which was to consider a number of complex and difficult measures on which there were considerable differences of opinion. The analytic approach used focused on a multiattribute value model that incorporated the views of many of the negotiating countries. This model was refined over the preparation period by both analysts and negotiators. The U.S. negotiators found that the model was useful for evaluating alternative proposals, anticipating and understanding the negotiating positions of other countries, generating promising compromise proposals, and communicating with other U.S. interest groups. The modeling effort helped the negotiators to identify a compromise proposal very similar to the one finally adopted by the Conference. As a result of the Conference important new international measures to improve the safety of oil tankers and help prevent pollution of the seas from ships were adopted.

Layout problems often involve a given number of facilities which must be located in the plane. Each of these facilities has a given area, and the cost of interactions between every facility pair is known. Problem optimality is achieved when facilities do not overlap and the total cost, which is the sum of weighted distances between all pairs of facilities, is minimized. The problem is formulated and solved as a nonconvex mathematical programming problem using a procedure termed DISpersion-CONcentration.

Is the link between performance and job satisfaction myth or reality? Does performance influence satisfaction, or does satisfaction influence performance? This age-old managerial problem is examined with a causal modeling methodology to unravel the true relationship.