Knowledge that Transforms

We present a tree-search algorithm for two-dimensional cutting problems in which there is a constraint on the maximum number of each type of piece that is to be produced. The algorithm limits the size of the tree search by deriving and imposing necessary conditions for the cutting pattern to be optimal. A dynamic programming procedure for the solution of the unconstrained problem and a node evaluation method based on a transportation routine are used to produce upper bounds during the search. The computational performance of the algorithm is illustrated by tests performed on a large number of randomly generated problems with constraints of varying “tightness.” The results indicate that the algorithm is an effective procedure for solving cutting problems of medium size.

In the past two decades researchers in the field of sequencing and scheduling have analyzed several priority dispatching rules through simulation techniques. This paper presents a summary of over 100 such rules, a list of many references that analyze them, and a classification scheme.

An easily-applied technique for measuring attribute importance and performance can further the development of effective marketing programs.

Can Personal Values be used to assist marketers in determining consumer choice behavior?